𝗔𝘁𝘁𝗲𝗻𝘁𝗶𝗼𝗻, 𝗔𝗴𝗲𝗻𝗰𝘆, 𝗮𝗻𝗱 𝗔𝗰𝗰𝗼𝘂𝗻𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆 are the “Triple-A”s of this era we live in. The things I think on are do we have them, know who has them, does anyone have them? Often the answer is no, and AI is making this worse - for now.

Let’s look at 𝘈𝘵𝘵𝘦𝘯𝘵𝘪𝘰𝘯 first, this is where we are seeing doom scrolling sucking our attention away, and removing the time to think, to apply our attention to the things we care about - I will come back to this.

But this is not the only attention sink - our early 20th Century business operating model is also built to pull us away from giving our attention to deeper thoughts - just look at the calendars from our senior leaders, and right through the organisation. What do we think about the productivity of a full calendar, rather than one with gaps - full calendar equals important person, right? Have we gamified our calendar like a Tetris game - how can we full in the gaps and win? A full calendar equals broken attention - is that what we want/need?

Most of our big thinking is done in the gaps - silence, stillness, and, dare I say, moments of boredom. And that brings me back to the social media attention sink. It is the perfect attention diverter - away from moments of silence, stillness, and boredom - away from opportunities for bigger thoughts.

Don’t get me wrong, these platforms - 𝘢𝘯𝘥 𝘐 𝘪𝘯𝘤𝘭𝘶𝘥𝘦 𝘵𝘩𝘪𝘴 𝘰𝘯𝘦 - have been setup and can contain great prompts for big thought - exposing us to other’s ideas and points of view. They allow for the exchanging and challenging of our assumptions - allowing us to question what we know and therefore grow our understanding and empathy. They can do that, but do we let them?

And, as always, we cannot have an article in 2026 without mentioning AI. This is where the slop comes in. It is hitting all the platforms we are talking about, making this exchange even harder, sometimes impossible. I scroll through and find perhaps 1-in-20 articles that are genuinely a commentary and thought from a person - and what is with all the AI Infographics lately? 😄

This is not a comment on what we are doing, we all have agency to choose how we engage (more on that below). I too use AI for some of my thinking - not in this case, mind - after all AI Transformation is my role - how and when is the key.

When I run training for leaders on AI, I start with the fear, uncertainty, and doubt around it - and the FUD is real. I cannot remove it, as they hope I will, but I can give it attention and context for them. The FUD is often based on potential reality - it could make us less skilled, remove creativity and tasks from our lives - it can do those things.

All is not hopeless, what I can share with them is that this is not a given and we still have 𝘈𝘨𝘦𝘯𝘤𝘺. We just need to consciously choose to apply it. We need to choose how and where we apply this new peripheral capability called AI. If we do not do this consciously (give it Attention), it will be applied to us, we will be abdicating our Agency and handing it to the platforms and the business think that surrounds us. Our opportunities for big thinking will be swamped by the gamified models of others.

You choose for yourself or it will be chosen for you, but either way, you choose.

Thus, we need to be 𝘈𝘤𝘤𝘰𝘶𝘯𝘵𝘢𝘣𝘭𝘦 and consciously choose when we use AI and what for. If you are up for it, take some of your precious Attention and, for you and your situation ask:

• What is taking my attention,

• How am I using it,

• What fills my days,

• What do I want to keep doing,

• What do I want AI to do for me,

• What does it do for me now (whether I want it to or not).

Take this information out of the cupboards and draws of your life and tip it all on the floor. Then KonMari what is there. Look for what “Sparks Joy” for you, individually, and think hard on how to keep it, water it, grow it.

This Accountability is important, for each of our personal lives, but we also have accountability towards others, society. I am accountable for what and how I am sharing with you. My actual thoughts, shared in a way that is understandable, meaningful, and, hopefully, 𝗰𝗼𝗻𝘁𝗮𝗶𝗻 𝗴𝗿𝗲𝗮𝘁 𝗽𝗿𝗼𝗺𝗽𝘁𝘀 𝗳𝗼𝗿 𝗯𝗶𝗴 𝘁𝗵𝗼𝘂𝗴𝗵𝘁𝘀 in you. Expanding back and forth between us humans, to a greater whole.

The AAA that allow for us to own our focus are important to contemplate on. Are we being 𝗮𝗰𝗰𝗼𝘂𝗻𝘁𝗮𝗯𝗹𝗲 for how we turn up, taking the 𝗮𝗴𝗲𝗻𝗰𝘆 to apply our 𝗮𝘁𝘁𝗲𝗻𝘁𝗶𝗼𝗻 in a way that grows us and those around us?

What I am writing could be unlocking the big thinking that only you, as a person, can open. I gave it my attention - the rest is up to you and yours.

Photo by Tim de Groot on Unsplash

The next Limitless Pivot is coming, soon, chaos will most likely ensue, but are we ready (hint, not likely).

We are currently obsessed with the word “agent.” I’ve been running AI Agent training across my org and always start with a simple premise: “We will likely stop talking about Agents entirely within 6 - 12 months - we will have moved on to their children.”

The word Agent implies a persona - a digital being with a mind of its own - agency. But the real signal in this technological shift isn’t the emergence of artificial life. It is the sudden, friction-less abundance of human intent - limitless human agency.

Moving from Agent to Delegate

We should stop talking about agents and start talking about delegates - the deliberate act of delegating human agency. This pivot in framing isn’t mine; credit goes to the philosopher Nicholas Lmblad. What follows, however, is my extension of that idea.

When we rename these flows as “Delegates” and “Delegation Flows,” the focus shifts immediately to the human providing the authority, the agency. It exposes the commercial and operational reality: we are no longer constrained by the physical limits of human time or the friction of administrative effort. We have moved from a world of scarce agency to one of limitless execution - and we have been here before.

The Lessons of Limitless Pivots

History shows us that whenever a physical or commercial limit is removed, the resulting chaos forces the creation of new operational disciplines.

Consider the music industry. A key limit was the CD - and the massive supply chain needed to get it into your hands. MP3 format, CD ripping shareware, and Napster removed that limit overnight, creating absolute chaos, market and creator/supply chain disruption, and limitless, uncontrolled supply. The eventual equilibrium - legislation, Apple Music, Spotify - didn’t just deliver the music; it delivered the governance, equitability for artists, and the new operating model required for a world without supply scarcity.

Even further back, connectivity followed the same pattern. When network availability moved from “best endeavours” to always-on, limitless connectivity. The resulting business expectations/shifts, and the commercial impacts on those expectations of any real downtime, necessitated the Network Operations Centre (NOC). And when this always-on world made cyber-attack vectors effectively limitless, we saw the birth of the Security Operations Centre (SOC). Both provided assurance and capability for value growth and sustainability. This innovation and growth is still being experienced and built on today.

The Erosion of the Limit

We are at that same limitless pivot point with AI. As Hannah Fry highlights in her recent exploration of “OpenClaw”, the barrier to entry for autonomous execution of our agency has vanished. A single developer can now unleash a “delegate” that can send thousands of emails, manage bank accounts, manufacture and ship products, and persist in a task long after a human would have tired.

The impact of limitless agency is larger than just our organisation - it impacts entire ecosystems. Most of our current industries are not just managed by limits - they are fundamentally predicated on them. Whether it is the physical capacity of a 40-hour work week or the cognitive limit of how many emails a person can reasonably process, these constraints act as the invisible scaffolding of our economy - again affecting supply.

By removing these “friction points,” we aren’t just making things faster; we are fundamentally disrupting sectors - from administrative intermediation to professional services and fulfilment - that rely on the fact that certain tasks are limited, difficult, or slow.

If a business assumes it is competing against a human-limited rival but is actually facing a limitless delegation flow, the competitive landscape is permanently altered. Equally, if thousands of personal delegated agents can each send through thousands of requests, 24x7, our limited workflows may not be able to cope with the demand and collapse. We are no longer just automating tasks; we are automating/delegating the “will” to execute them. Without a new layer of governance, the very commercial limits that define our markets will be eroded until only chaos remains.

This is not a doomsayer’s prediction (I know of made it sound like it though). It is an emerging commercial reality. It will be a reality sooner than we will like.

The resulting chaos will drive the need for the creation of new operational disciplines. However, in the chaos is real value.

The Great Unlock: From Effort to Outcome

The flip side of this disruption is an unprecedented expansion of capability. When we move past the noise of the risk, we find a world where the friction that has historically stifled some innovation simply evaporates. Abundant agency means we can finally tackle the “long tail” of problems that were previously too tedious or expensive to justify human attention - at the personal and macro scales.

Harvard Business School Professor Tsedal Neeley and Expedia Group’s Ritcha Gupta Ranjan argue that we are moving beyond simple AI assistance into a “higher order” of execution. They suggest that this shift toward agentic delegation is what will finally “unlock a 10x improvement in productivity.”

We are transitioning from managing effort to directing outcomes. The ceiling of our ambition used to be our stamina; now, it is simply our imagination. If we can master the delegation, we don’t just work faster - we work safely at a higher level of complexity than ever before.

But what is the framework, the NOC, of this current pivot?

The OC for Agency

If agency is now abundant, we must build the infrastructure and frameworks to unlock this safely - people, processes, and technology. We are already seeing the hyper-scalers creating platform capabilities, to support enterprise ICT - Microsoft’s Agent365 is a clear example - but this is just a tool. We need the frameworks that will utilise these tools.

So, once again, history repeats. Just as we have the NOC and the SOC frameworks ensuring the unlock of value from these limitless pivots, we now need a framework for agency - the Agent Operations Centre.

This AOC concept, pioneered by Jaime Enriquez and Fusion5 , is a framework for managing velocity. Like the NOC and SOC before it, the AOC doesn’t “do” the work for the business. It provides the context and people-based and process-based controls that allow the business to move faster, safely, at their own speed.

The New Role of ICT

The business has made the turn. They are tech-savvy, ready to execute, and - frankly - they’re not asking for permission anymore. They are wanting diffused decisions, capability, and innovation - at the speed of work. The question is whether ICT can make this turn too?

To remain relevant, ICT’s role is now sharper. There is a need to remain accountable, but now a growing role as the architects of the accountability guardrails, the distributors of safety and trust, and the auditors of the diffused estate. Empower the rest of the business to safely self-serve.

McKinsey & Company ‘s framing of the “Agentic Organisation“ - where humans sit above the loop rather than in it - is where this lands. In that world, the IT function becomes a governance engine enabling safe, rapid, diffused, People-led value and innovation.

Trust drives value

The business is already delegating to agents. The only question is whether we’re delegating safely, traceably, and on purpose.

If ICT wants to stay relevant, the work isn’t hoarding permissions - it’s designing the guardrails and capabilities (people process and technology capabilities) that make distributed execution viable and visible: clear authority, non-human identity and RBAC management, and continuous audit. That’s foundational to what an AOC must provide.

Because soon, the scarcest resource won’t be effort, it will be trust and confidence. And the organisations that can manufacture confidence - consistently and systematically - will realise the great unlock and outcompete the ones that can only manufacture output.

Photo by Roger Bradshaw on Unsplash

TL;DR: The “right-click deploy” world of SaaS and AI means business units no longer wait for ICT - they just subscribe. But while the capability to move fast has shifted to the business, the accountability for the associated risks (like cyber safety, PII, and data ROT) has been left behind. This massive gap is breeding accountability avoidance, risking value innovation.

The solution isn’t throwing another governance policy at the business; it is providing them with true agency. ICT must shift from being a traditional gatekeeper to an enabler, providing the context, tooling, and “hidden safety rails” that allow our digitally savvy peers to visibly own, manage, and safely execute on their decisions.

The “right-click deploy” world has arrived.

These days, ICT no longer has the monopoly on digital skills. The model has fundamentally changed this millennia - digital natives are now spread across the entire organisation. So, what is next for ICT-business relations?

Business units no longer wait for ICT to build tools; they reach for their credit cards and subscribe to the future. A lot of our thinking, expectations, and control mechanisms have not moved with this change. Because of this, there is a hidden friction in this new speed: a massive accountability and decision gap.

Business leaders want to move capability and decisions closer to the work. It makes sense, but, without the wider context, we have a large gap in understanding around accountability and responsibility. Without this clarity, we in ICT naturally resists. After all, baked into our bones is decades of understanding and responsibility regarding the risk and safety of technology use, and we are not currently seeing anything in this new “credit card” approach that alleviates those concerns.

This is not an “us vs them” scenario, or even a “Shadow ICT” (and now “Shadow AI”) challenge - although those are certainly the symptoms. This is a profound lack of clarity around accountabilities and the responsibilities that come with them. If the business can deploy SaaS services with little or no need for the tech teams’ involvement, what are each (business and ICT owners) accountable for now - and to whom?

The Missing Pieces of the SaaS Migration

Don’t get me wrong here, I am totally for moving this decision closer to the work. For the business to move fast, they need the freedom to make decisions closer to the coalface than traditionally provided by the old accountability models.

The business wants to lean into the direct relationship with the SaaS vendor, and fair do. They are digitally savvy, after all, and this is not a large technology deployment anymore. It is a configuration exercise - and mostly, it is business capability configuration.

But, what accountabilities are not being moved with that configuration?

What about PII risk? Cyber safety and reputational risks? Technology redundancy and obsolescence costs? Data quality and ROT (Redundant, Obsolete, Trivial data)? If the business assumes they do not own these, and ICT assumes they do, what then?

I think one of the fundamental challenges here is that we have not actually paused to talk, and consider and articulated these accountabilities. We haven’t asked who owns them, and why. Nor have we checked if we all even agree that they are still real, relevant, and right in this modern context. Without this understanding, we Ass-U-Me.

Agency: The Antidote to Avoidance

Unclear accountabilities in this new SaaS world present a fundamental challenge to opening up business self-service safely. Starting a conversation on these opens up opportunities for acceptance, understanding, and collaboration, as trust and assurance start to grow across the whole business.

But a conversation is not enough. It needs to come with the capability to action.

For a business leader to truly accept responsibility for adding, changing, or growing a new platform - and the related accountabilities that come with it - they must first have the visibility and capability to manage those associated risks - they need agency.

Accountability without agency is just a recipe for avoidance - and this is exactly what we are seeing today.

This isn’t about throwing a governance manual or policy at a business unit and wishing them luck. Governance is just one of the tools we have. This is about agency.

The new ICT enablement game isn’t about “doing the IT” for the business - that has mostly gone with SaaS. It is about providing the context and tooling that allows the business to see and manage the risks they now own and decisions at the speed they choose to move.

ICT will have a clear, understood, and agreed set of accountabilities too, the Board is still looking to the CIO for assurance across our ecosystem. I am sure that these new era accountabilities are now less onerous than we are assuming from our past, pre-SaaS experiences. We are no longer protecting the digitally ignorant - these are our digitally savvy peers.

ICT’s role shifts from a gatekeeper to a provider of context and platform “safety rails.”

This architecture allows a business leader to own, and have agency for, their data inputs and outcomes, and the related quality, because the context is visible and the management is simple and attainable. ICT maintains its own accountability to the board - managing platform risks, security, and systemic integrity - while empowering the business to drive forward safely.

Shifting the Dial: From Gatekeeper to Enabler of Value

Take AI as a hot conversation that is currently sitting right in the middle of this change. As highlighted in the Deloitte “State of AI in the Enterprise 2026“ report, the gap between AI deployment and governance maturity is widening. Only 21% of organisations have a mature model for the autonomous agents they are currently deploying. The end result? “Shadow AI” and accountability gaps (and related risks) appearing throughout the organisation.

ICT has a key role to play in bridging this gap with the right context and tooling for the business owners of these agents - delivering Safe Self-Service capabilities. You own it and have agency to manage it.

I relish this as a technologist. So often, the unstated thought is “I don’t know how the tech works, so this is ICT’s problem” simply because the actual owner of the application, data, and outcomes does not know, nor have the ability to affect, these things. Historically, only ICT did.

This change moves that “Ownership” of the problem exactly where it should be: with the people who have a stake in the outcomes.

I have seen what happens when this agency is achieved in real life. When you share the context with the actual business owner, and give them the ability to influence it, they lean in - way in. The avoidance we see is not about pushing away from responsibility; it is simply this lack of agency.

To be clear, I don’t think there are any bad actors in this situation. The landscape has changed, but our ways of farming it have not. We all want this clarity.

By baking this “Accountability by Design” into our thinking, from the exec tables down, and into the tools themselves - through automated auditing, transparent reporting, most-things-as-code, and clear workflow - the business is truly empowered. They can safely and visibly make context-driven decisions, generating value without the fear of hitting a “hidden” regulatory or risk cliff ahead.

What if ICT empowers and enables this? We unlock the ability for the business to reach for the new value they are looking for, as and when they need, through safe self-service - agency.

Five Strategies for Integrated Accountability

So, how can we approach this practically? MIT Sloan Management Review recently published a set of five strategies that outline a framework we should think on: “The Three Obstacles Slowing Responsible AI“.

While their focus is Responsible AI, these strategies should be considered for the wider “right-click deploy” SaaS ecosystem - after all, AI is simply becoming an embedded part of this ecosystem anyway.

To move decisions closer to the work effectively, we must adopt these five strategies for “Ethical Judgment” over simple compliance:

• Structure Ownership at the Point of Impact: Shift the “Who owns the risk?” question from the IT department to the business lead, who actually owns the outcome.

• Hardwire Guardrail controls into the Tooling: Use platforms that provide “audit-as-you-go” capabilities, so compliance is a by-product of the work, not a burdensome extra step - building visibility and trust.

• Align Ethical Risk with Business Risk: PwC’s 2025 RAI survey shows 58% of leaders see RAI as a tool for positive ROI. Safe AI is simply more profitable AI. (While this is RAI specific, it has wider implications as an approach that provides the oversight needed in this rapidly changing SaaS ecosystem we are now in.)

• Reward Responsible Innovation: Foster a culture where “right-click deploy” is celebrated because it happens within a governed framework.

• Practice Ethical Judgment: Move the conversation from “Is it legal?” to “Is it right for our context?” This requires specialists embedded in business squads, not hidden away in an ICT ivory tower.

The New Architecture of Trust

When I understand what I am accountable for - whether I am the business owner or the ICT enabler - I can understand, and articulate to others, what I need in place and why. I can trust moving the decision boundary closer to the work.

Simple, efficient, and effective capability allows the business to articulate why they need a specific move and what controls they have in place to manage it. This isn’t about red tape; it’s about the articulation of safety that allows us to go faster with assurance.

As Wolters Kluwer noted in February 2026, “Speed vs. defensibility is a false choice“. When the guardrails are baked in, you don’t have to slow down to be safe.

Upfront “Accountability by Design” isn’t a handbrake; it’s the scaffold that allows the business to scale safely and with speed. ICT’s new role is to enable safe, transparent, fast value. To provide the business the context and tools that make owning the risk accountability as simple as clicking “deploy.”

This is about the Why, What, and Who of accountabilities - once we have this the How becomes clear and straight forward.

Photo by Roberto Cosentino: Pexels

The transition into the Intelligence Era is often framed as a technical revolution, yet for those of us standing at the intersection of business, craft, and technology, it feels profoundly analogue and personal. We are currently witnessing a period of high-frequency friction - a collective “flinching” from the unknown. This hesitation is often mislabelled as fear, but it is more accurately described as a deep respect for the human element in our work and what next for this. We are protective of the nuance, the grit, and the “soul” that defines excellence, whether in a cinematic frame or a legal brief.

The current news cycle offers us a perfect “tell” to examine this transition. Darren Aronofsky, a director synonymous with visceral, human-centric storytelling, has launched Primordial Soup, a studio dedicated to exploring the boundaries of AI-generated content. The critical reception to his series, On This Day... 1776, has been polarised, with many pointing to the “uncanny valley” and the plastic nature of the output.

However, looking only at the aesthetic “slop” misses the strategic point. Aronofsky is practicing what I call The Emerging Tech Antidote (or should it be the Aronofsky Antidote?): the choice to experiment openly and learn through engagement rather than retreating into the stalls. This isn’t about the technology being ready; it is about the human being ready to understand the technology.

1. The Artistic Arc: Learning Through Engagement

There is a valid and necessary discourse surrounding the use of AI in art, particularly concerning IP training and the potential displacement of roles. To dismiss these concerns as “fear” is to ignore the ethical gravity of the situation. Instead, we must look at how artists are using experimentation to move from abstract anxiety to grounded understanding.

Aronofsky’s foray into AI is not a declaration that the machine has “arrived.” Rather, it is a public stress test. By launching Primordial Soup, he is moving from Black Box technology - where we wait for a polished product to be handed to us - to Glass Box experimentation. He is finding the “hallucination threshold” and what new could look like.

When an artist of his calibre puts their name on an unpolished experiment, they are essentially rebranding the “uncanny” as a new cinematic grammar. They are identifying exactly where the machine fails, so they can double down on where the human must lead. Research into Generative Synesthesia suggests that the real value of AI in the creative process isn’t the final output, but the way it forces the creator to refine their own ideation and filtering skills. The machine provides the “soup,” but the artist provides the “recipe.” Have a look at this MOMA video, “How Artists Are Rewriting AI’s Future“, for a great example of this.

2. Historical Anchors: The Expansion of the Creative Horizon

It is vital to recognise that we have been in transition states like this before. The arrival of a new medium does not signify the death of a skill; it signifies its evolution and, often, its democratisation and the expansion of new skills.

The Gutenberg Shift

When the printing press arrived, the immediate concern was the death of the scribe. The physical act of monk-led calligraphy was a more specialised, high-art form, resulting is niche access to complex art. Gutenberg democratised access to the written work. and the world gained the new role, Author. The value migrated from the physical beauty of the page to the intellectual property of the ideas within it. It allowed stories to be read by millions, opening the gates of knowledge to those who previously had no access.

The Photography “Crisis”

In the 19th century, painters feared photography would make their craft obsolete. If a machine could capture a perfect likeness in a fraction of a second, why spend months on a portrait?

History shows us that photography did not replace the painter; it liberated them. It gave birth to Impressionism and Expressionism. Because a machine could now capture objective reality, painters were released from the ‘shackles of realism’ and were free to explore the subjective human experience - light, motion, and emotion. Simultaneously, photography opened the door for a new kind of artist: the photographer, who might have possessed a cinematic “eye” but lacked the physical dexterity required for oils.

In both instances, the original craft remained a valued, specialised pursuit, while the new tool expanded the boundaries of what was possible for the collective - widening, democratising and enriching for us all. We are in a similar expansion today. The “Intelligence Era” is not a replacement for human talent; it is a new medium for those with the vision to use it - and it is coming regardless.

3. The Intellectual Pivot: From Execution to Contextual Lead

The journey the artist is taking is the same one facing every knowledge worker today. Whether you are a lawyer, an accountant, or a strategist (yikes!), the FUD (Fear, Uncertainty, Doubt) is the same. The anxiety isn’t that the work will disappear, but that the “how”, the tasks, of our work is shifting beneath our feet and what that means for our sense of identity and purpose.

We must move away from the idea that we are becoming menial “orchestrators” or “prompt engineers” - we are not the tasks. These terms are derogatory and fail to capture the complexity of the transition. Instead, we are becoming Contextual Leads.

As AI takes over high-volume, low-context execution - drafting the first version of a contract, summarising a 200-page report, or running basic financial simulations - the human role intensifies around critical thinking, ethics, and contextual judgment.

• The Auditor: A lawyer is no longer just drafting; they are auditing a machine-generated brief for nuanced legal risks that only a decade of experience can detect.

• The Interpreter: An analyst is no longer just crunching numbers; they are interpreting what those numbers mean for a specific community or corporate culture.

• The Curator: A strategist is no longer just brainstorming; they are curating a sea of AI-generated options to find the one that aligns with human values and long-term brand integrity.

The work isn’t disappearing; it is migrating to the “High Ground” of accountability. A machine can provide an answer, but only a human can provide the “So What?”- AI Amplification of our purpose.

Every technological leap may kill the “how” but amplifies the “why.”

4. Governance: Who Owns the Risk?

In this new era, the primary risk is no longer technical; it is Curative Risk. This is the risk of a high-authority brand putting their name on “slop” because they haven’t yet learned how to provide human oversight - this is where the experimenting and learning comes in.

This leads us to the concept of Safe Self-Service and ICT’s new role in the SaaS world in general. We are seeing business units wanting to do their own AI. After all, it is baked into the platforms they use everyday - easy, right? The traditional role of ICT is shifting from “doing the IT” to providing the framework for audit and safe enablement.

Governance in 2026 is about answering a key question: Who owns the hallucination? If an AI makes a mistake, and we use it, the accountability cannot be outsourced to the software vendor, or, as is often the case, ICT. It must sit with the Contextual Lead in the business who approved the output. This is why Aronofsky’s experiment is so vital; it is the only way to build the “intellectual muscle” required to spot the machine’s errors before they reach the market. This applies equally in business and technology.

A machine can provide the answer, but only a human can provide the “so what?”

5. Resolution: The Call to Agency

The transition into the Intelligence Era is not a spectator sport. To move past the FUD, we must adopt the Emerging Tech Antidote (I still prefer, Aronofsky Antidote). We must be prepared to experiment and learn, to get it wrong, and to fail in private playgrounds so that we can succeed in public arenas.

We should not wait for the “perfect” version of these tools, or for them to fail and go away (that’s not going to happen). If you wait for AI to stop hallucinating or for the “uncanny valley” to disappear, you will be a spectator to those who have already learned how to navigate these flaws.

What next?

The path forward is Experimentation as De-risking.

1. Identify your “Primordial Soup”: Where can you experiment with these tools in a low-risk, high-learning environment?

2. Audit the “Tell”: Where does the machine fail in your specific industry? What are the “plastic faces” of a machine-generated legal brief or marketing plan?

3. Elevate the Role: Stop viewing yourself as a producer of tasks and start viewing yourself as a Contextual Lead. Your value lies in your judgment, your ethics, and your ability to say “No” to the machine. The “Human-in-the-Loop” is no longer a safety feature; they are the primary source of value in the chain.

Where is the human oversight?

Importantly, in an era of abundant synthetic content, the only remaining scarcity is human taste and ethical accountability. We must ensure that as the tools of creation are democratised, the skills of critical judgment are protected and prioritised.

The future belongs to the Contextual Leads who are brave enough to let the machine fail in their hands today, so they can lead it tomorrow. Start your experiment, and find the human ‘tell’ in your work.

Photo by @girlwithredhat unsplash

This is it. We’ve reached the final post in the “Facing the Elephant” series.

We started by naming the elephant: the 80-90% of our data that is unstructured and we all ignore.

We saw how, like the blind sages, our leaders in Finance, ICT, and Risk are only able to see their own part of the problem.

We watched the “rising tide” of the modern, collaborative ways-of-working, and the tools enabling it, showing why the elephant grew so large. The beast being fed by the frictionless creation of content in tools like Teams and Slack.

We opened the closet on the “skeletons” – the obsolete decisions, outdated standards, and sensitive data lurking in there, all invisible to traditional governance.

And last week, we saw how GenAI is the “double-edged sword”: the catalyst that finds every skeleton - security by obscurity is dead - but this also provides the powerful business case to finally unlock the executive focus and budget we’ve always lacked to tackle this.

The blind sages can now step back and collaborate. We see the whole elephant - together.

And it’s huge. It feels overwhelming, even insurmountable. So, what on earth do we do now?

How to Eat the Elephant

“The only way to eat an elephant is one bite at a time.”

That is how we must approach unstructured data. The feeling of being overwhelmed comes from trying to boil the ocean - treating this as one monolithic “IT project”.

It’s not. It’s a business priority and problem to solve, and it requires a new approach. That path forward is built on three “bites”, taken in order: Strategy, Governance, and Automation.

Bite 1: Strategy (What Matters?)

You cannot govern what you cannot see and do not understand. The first bite isn’t about technology; it’s about people priorities.

Before you buy a tool or start a “clean-up”, the business must answer one question: What matters?

Stop trying to manage everything. Start by identifying and classifying what matters most. This includes:

• High-Risk Data: Where are your skeletons? Find the sensitive PII, commercial IP, and regulated data.

• High-Value Data: What data will actually make your AI tools smart? Identify the “golden” datasets, the current standards, and the approved policies.

• The ROT: (Redundant, Obsolete, Trivial). This is the 50%+ of your data that’s just noise. This isn’t an ICT task. This is for business leaders to define. Hint: it also messes with your enterprise GenAI quality!

Bite 2: Governance (Who Owns It?)

Once you can see what matters, the next bite is accountability. For decades, unstructured data has been everyone’s responsibility and therefore no one’s - or worse, “Oh, that’s an IT problem, what are you doing CIO?”

Governance means assigning clear ownership - who’s data is it? It means creating simple, enforceable rules for the data identified in Bite 1. This isn’t just about retention; it’s equally about disposal.

We must make “delete” a confident and positive action, not a fearful one. This step transforms governance from a dusty policy document into an active, accountable business function.

Bite 3: Automation (How Do We Enforce It?)

This is where technology finally comes in (NOTE, it should always be technology last - People, Process, then Technology). The “rising tide” of data is too large for manual efforts - I am talking to you King Canute.

Once you have your Strategy (you know what matters) and your Governance (you know who owns it and what the rules are), you can finally apply Automation.

You use platforms to automatically enforce the rules, protect the high-risk data, and surface the high-value data for your AI. Importantly, the tools provide the business context and visibility for the actual data owners to make informed decisions.

The technology becomes the enabler of your business strategy, not just a frustrated digital janitor. And fortunately, there are platforms now that will dare to stare into the unstructured closet, and assist and automated addressing it. Hmm, is it closet or is it a floordrobe?

Facing the Elephant, Together

The core theme of this series is that this elephant cannot be faced by one person or one department. For too long, the business has created the “rising tide” of data, and ICT has been left to drown in it.

The path forward is one of collective leadership:

• Business Leaders must stop seeing this as an IT problem. They must step up to own the Strategy (Bite 1) and the Governance (Bite 2) - and their own unstructured data.

• ICT Leaders must provide the platforms and visibility to provide the transparency, visibility, and capability to enable those business decisions and deliver simplification through sustainable, managed Automation (Bite 3).

• Risk and Compliance must act as the guides, embedding practical, automated controls into the process, not just auditing the failures - someone has to manage this process.

The elephant in the room hasn’t shrunk. But by standing together, with a plan, the right governance processes, and enabling tools, we’re no longer blind.

It stops being an invisible, terrifying monster. It becomes visible. Manageable. And finally, by clearing the path for AI and innovation, it becomes valuable.

Call to Action

Thank you for following this series, a passion of mine and I am pleased to see, at least in our organisation, we are daring to look.

Now, I ask you: What is the first ‘bite’ your organisation needs to take?

Photo by Francesco Ungaro: Pexels

In this series, we’ve walked around the elephant in the room: unstructured data.

• In the first post, we named it – this massive, invisible problem that different leaders see only in part, like the blind sages.

• We watched the “rising tide“, the relentless flood of content from the very collaboration tools we use to be productive.

• And last week, we opened the closet and found the “skeletons“ – the sensitive, outdated, and risky data lurking in the unstructured soup.

The Veil has been Cut Away

For decades, we’ve relied on “security by obscurity”. We hoped that as long as this data was buried deep enough in old file shares and forgotten email threads, it was effectively safe. The problem was way to hard to look at, let alone address.

Now, that assumption is dead. Generative AI is here, and it’s a double-edged sword.

The Curse: The Blade We Can’t Ignore

The “curse” of GenAI is simple: it will find everything.

Tools like Microsoft Copilot and Google’s Gemini are designed to read, summarise, and connect all the information you give them. They are not looking for key words, but semantic inference, they understand the context of the content. Importantly, they will not distinguish between a current, approved policy and an obsolete draft from 2015. They will not recognise that a spreadsheet of customer data saved in a personal chat is a privacy breach waiting to happen.

When your AI surfaces this “dark data,” it doesn’t just create a security risk; it creates a strategy-corrupting risk.

Your shiny new AI tool, fed on a diet of unstructured soup, will:

• Contradict current strategy with obsolete decisions.

• Pollute insights with outdated standards.

• Expose sensitive IP, financial records, and personal data.

This is the sharp edge of the sword. It’s the risk from Post 3, now unveiled by AI.

The Blessing: The Handle We Can Finally Grip

Here is the strategic pivot: this curse is also a profound blessing.

For years, ICT, Risk, and Compliance leaders have tried to get traction on data governance. We’ve used the “blind sages” parable, pointing to cost, risk, and complexity. But it’s been a hard sell - an infrastructure problem, cost with no business value, not a business-critical priority.

GenAI has changed the conversation overnight.

When I talk with the C-suite they are no longer asking if we should use AI; they are asking how fast we can deploy it. They see the elephant now and they understand it is getting in their way.

Suddenly, governance is no longer a cost centre. It is the essential prerequisite for innovation. You cannot safely and effectively use Copilot or Gemini if your data estate is a minefield of skeletons.

This is the blessing: GenAI provides the single most powerful business case for information governance we have ever had. It unlocks executive focus and, crucially, executive budget. It’s the forcing function that finally makes the invisible elephant visible to everyone.

The Takeaway: The Best Chance We’ve Ever Had

The threat of GenAI surfacing our messy, unstructured data is the best chance we’ve had to face the elephant and address it.

It reframes the entire problem.

• Before: “We need to clean up our data to reduce risk.” (A cost)

• Now: “We need to govern our data to unlock AI value.” (An enabler)

The sword is in our hand.

Wielded badly, it will expose every risk we’ve ignored.

Wielded correctly, it’s the tool we can use to cut through the complexity, tame the elephant, and finally turn decades of dark data into a strategic asset.

Call to Action

The time for ignoring the elephant is over. The sword is here - do we move the metaphor to Damocles? 🤔

If you had to make your unstructured data estate AI-ready today, where would you even begin?

Photo by Zain Abba: Pexel

The hidden risks lurking in our unstructured data - and why GenAI will drag them into the light.

We’ve seen the elephant in the room, unstructured data, the 80–90% of information that never makes it into dashboards.

We’ve felt the rising tide, the relentless growth driven by collaboration, culture, and the frictionless creation of content.

Now it’s time to open the closet.

Because hidden inside that tide are skeletons - forgotten files, sensitive data, risky documents - that most organisations don’t even know they’re storing. And with GenAI about to illuminate every corner of our information landscape, the days of “out of sight, out of mind” are over.

Security by Obscurity Is Dead

and so is the illusion of “Safe” Data.

For decades, we’ve relied on a quiet, often unspoken assumption: if sensitive data was buried deeply enough - in archived email threads, old SharePoint sites, or long-forgotten network drives - it was effectively safe. Nobody could find it, so it is not a risk.

That assumption no longer holds.

GenAI doesn’t distinguish between current and obsolete, relevant and outdated, approved and deprecated. It reads everything — and in doing so, it surfaces everything. That doesn’t just include sensitive information. It includes old decisions, superseded designs, obsolete policies, outdated standards, and past strategies that no longer reflect how the organisation operates today.

When those artefacts are surfaced without context, they don’t simply confuse - they can contradict current policies, cloud governance decisions, and pollute AI-generated outputs with incorrect or conflicting information. The result isn’t just exposure; it’s distortion.

My own experience and recent large-scale analysis across 1,000 real-world environments found that 90% of organisations have exposed sensitive cloud data and 99% have sensitive information dangerously exposed to AI tools — a visibility problem as much as a security one.

What’s Lurking in the Shadows

Every organisation has skeletons hiding in its unstructured data. These go far beyond PII or compliance data:

• Sensitive personal information: CVs, ID documents, medical details, tax numbers.

• Legacy decisions: strategy and policy papers that no longer apply, or even just old drafts, may still influence thinking.

• Outdated standards and designs: technical documentation, old technical designs, or product plans that conflict with current approaches.

• Regulated data: privacy-covered content embedded in chat logs, emails, or PDFs.

• Shadow datasets: exports from SaaS platforms no one remembers storing.

IBM’s Cost of a Data Breach 2024 found customer PII was the most frequently compromised data type (≈46%), underscoring how often “ordinary” content becomes high-risk when it leaks.

And Varonis’ 2025 study shows the operational reality many teams face: 90% of organisations have sensitive files exposed to all employees via M365/Copilot - exactly the kind of context-free resurfacing GenAI accelerates. I love this semantic search capability in Copilot, just quietly.

The Cost of What We Don’t See

The consequences are getting harder to ignore:

• Regulatory fines: GDPR enforcement remains heavy; across 2024, fines totalled roughly €1.2 billion, per CMS’s Enforcement Tracker analysis of monthly penalties.

• Legal exposure: resurfaced, superseded clauses or contracts can re-open dormant liabilities.

• Reputational damage: incidents involving archived or obsolete data make organisations look careless, not unlucky.

• AI mistrust: when a tool like Copilot elevates a deprecated standard or an old decision as “fact”, confidence in GenAI plummets.

High-profile cases in late 2024 and 2025 (e.g., large platform fines; collaboration-tool breaches) only add pressure for visible, defensible governance.

All of this slows us down, brings hesitancy in decisions around embracing this burgeoning Intelligence Era, and can result in lost opportunity, or direct market impact as we fall behind better prepared competitors.

Opening the Closet: A New Kind of Governance

The answer isn’t to avoid GenAI - it’s to prepare for it. Governance isn’t about slowing innovation; it’s about making innovation safe.

That means:

• Visibility: Audit and classify data across collaboration platforms, file shares, and archives.

• Control: Implement clear retention, deletion, and access policies - and actually enforce them.

• Readiness: Assume AI will see and use everything. Build guardrails (policies and standards for labelling, DLP, access hygiene) accordingly.

It’s telling that improving unstructured-data governance is now a board-level priority for nearly half of organisations, according to a 2024 industry survey.

Hope: Light Is Better Than Darkness

Yes, this is uncomfortable, opening the closet always is, but it’s also empowering.

Once we know what’s there - once we’ve named the skeletons - we can decide what stays, what goes, and what must be protected.

That knowledge turns AI from a threat into a tool. It lets us pursue automation and augmentation with confidence. And it transforms governance from a compliance exercise into a strategic enabler.

The age of security by obscurity is over. The era of informed, intentional governance is just beginning.

Call to Action

How confident are you that you know what’s hiding in your unstructured data - and would you trust AI to read it all tomorrow?

In the next post, we’ll look at why GenAI isn’t just a risk, but also a remarkable opportunity - the double-edged sword that could finally help us bring this elephant under control.

Photo by Carlos Felipe Ramírez Mesa: Unsplash

In the first post of this series, I called out the elephant in the room: unstructured data. It makes up the majority of enterprise information, yet is often invisible to leaders - and thus, often avoided.

Today, I want to look at how that elephant grew so large - the rising tide that feeds it.

A Tide That Won’t Stop Rising

Unstructured data is at the core of our working lives. While structured systems run the business, we are constantly creating, sharing, and storing unstructured information. Every Teams ping, email thread, shared drive folder, or Zoom recording adds to it.

And it is relentless.

By 2025, unstructured data already accounts for over 90% of business information (Athento, 2025). IDC forecasts global data volume reaching 181 zettabytes this year, with the vast majority unstructured (DemandSage, 2025). Nearly 90% of that remains “dark data” - stored but never used (TechRadar, 2025).

What was once a manageable file share is now a multi-petabyte estate. And unlike structured data in systems of record, this tide spreads across dozens of apps and silos, beyond the reach of traditional governance. Out of sight, out of mind.

Why It Keeps Rising

1. Collaboration Explosion

2. Low Barriers to Creation

3. Culture of “Keep Everything”

4. AI Readiness Pressure

What the Rising Tide Means

Every part of the business feels the impact:

• Business & Finance feel the cost of storage and backup as estates swell.

• ICT feels the operational strain: migrations, outages, and ballooning infrastructure bills.

• Risk & Compliance feel unease as sensitive data is swept along, often unnoticed.

• Strategy & AI Leaders see the promise of Copilot or Gemini, but know that if the tide is full of ROT, AI will surface that too.

This is the dangerous truth: the tide is rising across every part of the business, yet no one group owns the responsibility for managing it. Content creators? Data owners? Platform owners? Risk managers? Everyone touches it, but no one governs it.

The Metaphor That Matters

Think of it this way:

• A trickle can be ignored.

• A flood demands attention.

• A tide never stops.

Unstructured data is that tide. Left unmanaged, it rises relentlessly, seeping into every corner of the organisation. The elephant we identified in the first post in this series didn’t appear overnight - it was fed by years of rising waters.

What We Can Do

We can’t hold back the tide entirely. Collaboration, communication, and digital creation are the lifeblood of modern work. But we can:

• Build smarter levees: retention policies, classification, and lifecycle rules.

• Drain the swamps: disposing of ROT and duplicates to reduce volume.

• Channel the flow: directing high-value data into governed repositories where AI can generate real insight.

These are not easy tasks, but they are achievable - and each step lowers the water level.

What next? Hidden Depths

In the next post, we’ll look at what’s lurking beneath the surface - the skeletons in the closet hidden in this tide: sensitive information, contracts, and personal data that AI will surface whether we’re ready or not.

Call to Action

Tell me, where is the rising tide felt most strongly in your organisation - endless chat threads, forgotten file shares, oversharing, or ballooning cloud storage bills.

Photo by Ray Bilcliff: Pexel

We call ourselves data-driven. Dashboards glow, KPIs tick upwards, and AI pilots are everywhere.

Yet there’s an elephant in the room: most of our data isn’t in those dashboards at all.

Analysts estimate that 80–90% of new enterprise data is unstructured — sitting in emails, chats, files, videos, and collaboration tools (Felicis, citing Gartner & IDC).

It’s large, messy, and growing fast. And when it comes to managing it, most of us would rather look away - are looking away.

I am calling out this elephant, we need to look at it.

Why It Matters — Different Viewpoints

Business & Finance: Cost Without Control

Unstructured data eats into budgets. Surveys show that 62% of organisations see opportunity in unstructured data for operational efficiency, yet nearly 70% admit they’re not well equipped to leverage GenAI on it (Qlik/ETR Survey, 2024). That means spend without return, investment without clear value.

ICT & Operations: Scale Without Visibility

Industry reports highlight growth rates of 55–65% annually for unstructured data (Nexus Frontier - 2021, mind). At that pace, yesterday’s manageable file share becomes today’s multi-petabyte problem. ICT teams feel the pressure in backups, migrations, and infrastructure planning — but often lack clarity about what the data contains, and importantly, lack the attention and resourcing to address this.

Risk, Legal & Compliance: Exposure Without Awareness

Unstructured stores are where sensitive information lurks. A Komprise 2024 survey found that 47% of organisations rank governance and security of unstructured data as their top capability need (Komprise Report 2024). Regulation doesn’t forgive ignorance: GDPR, CCPA, Privacy Act 2020 (NZ), and sector laws expect clarity and control. Without visibility, compliance is a gamble.

Strategy & AI Leaders: Promise Without Readiness

We’re told AI will be transformative. But “dark data” — unstructured and underutilised — makes up around 90% of enterprise information (TechRadar, 2025). If that dark data is messy, duplicative, or unclassified, then Copilot or Gemini risk amplifying noise as much as insight. Instead of accelerating progress, AI may shine a spotlight on risks we’d prefer remained hidden.

The Blind Sages and the Elephant

An ancient parable tells of blind sages encountering an elephant for the first time.

• One touches the trunk and insists it’s a snake.

• Another, the tusk — clearly a spear.

• Another, the leg — surely a tree.

Each perspective was valid. Yet without context, each was incomplete, and none grasped the full truth. That’s us with unstructured data.

• Finance touches the budget and feels only the drain of cost.

• ICT touches the petabytes and feels only the complexity of scale.

• Risk & Compliance touch the regulations and feel only the exposure.

• Strategy touches AI pilots and feels only the promise wasted.

Each view is real, but partial. No one sees the whole elephant. And as long as we act separately, we misunderstand both the scale of the problem and the path forward.

Setting the Stage

This is a theme I want to lean into and discuss here. Over the coming posts, I’ll explore different parts of this elephant:

1. How the unstructured tide has grown so large.

2. What risks it hides in plain sight.

3. Why GenAI is both a curse and a blessing.

4. And how all parts of the business and ICT can face the elephant together.

Step by step, we’ll build a fuller picture.

Hope: A Way Forward

I am not all doom and gloom, in-fact that is why I am writing this. We can get control, we can get context, we can turn this elephant to value — together. Yes, the elephant is big. But it isn’t immovable.

There’s another saying: the only way to eat an elephant is one bite at a time.

That’s how we must approach unstructured data. Start small:

• Tag and classify what matters most for AI readiness.

• Dispose of obvious ROT.

• Protect the highest-risk data first.

Each bite reduces risk, frees cost, and builds trust. And as business, ICT, risk, and finance align, the elephant stops being invisible. It becomes visible, manageable — and finally, valuable.

Call to Action

What part of the elephant does your organisation feel most strongly today — cost, risk, complexity, or lost opportunity?

In the next post, we’ll look at where the unstructured soup comes from — and why it keeps growing faster than we can manage.

Photo by Francesco Ungaro: Pexels

TL;DR

AI today is noisy - hyped, hyped again, and tangled in fear and confusion. But beneath the buzz lies a very real shift: the transition from solely bespoke creation to everyday configuration. My North Star is simple: stay grounded, focus on value, and empower the business to use AI wisely, every day - across every function, not just in labs. This isn’t about replacing technologists — it’s about evolving our role, enabling others, and quietly leading the shift. This is the Intelligence Era — and we’re already in it.

Making AI Normal

AI is having its Cloud moment.

Like Cloud in the mid-2010s, it’s talked about everywhere, and yet still misunderstood. We’re being hit by a tidal wave of hype, inflated promises, and looming uncertainties. It’s messy. It’s noisy. And it’s easy to get distracted.

So, what do we do?

We look through it. We stay focused on what actually delivers value.

Two Pillars: Create and Configure

I see we now have two distinct - but connected - pillars of AI:

1. Create - The traditional world: bespoke model-building, deep data science, and custom solutions. Complex, high-value, solid - decades in the making - body of knowledge, and still essential, but not always the fastest path to impact.

2. Configure - The emerging space: platforms like Microsoft Copilot Studio, Salesforce Einstein, and ServiceNow AI. These tools let business teams build what they need directly in their business platforms - no specialist required.

We’re not replacing one with the other. We’re layering them. The real opportunity is in using both wisely.

Creation Is Evolving, Not Ending

The rise of Configure doesn’t make Create obsolete - it reshapes it.

We’re seeing AI used to build AI. Agents writing agents. Copilots generating code. ChatGPT designing entire data workflows. What once required weeks of expert effort can now be kicked off with a prompt - the specialist now has digital colleagues to extend their capabilities, and remove drudge.

But this shift doesn’t mean we’re phasing out technologists. Quite the opposite. Their role is evolving - from just builders to enablers, from just hands-on to hands-around. As Microsoft says in their Future of Work research - evolving towards being the Boss of your own AI cohort. We still need architects and engineers to ensure quality, security, ethics, integration. They’re the ones who guide the use of these new tools responsibly and effectively - AI Bosses.

This is not a sunset on our roles. It’s a horizon expanding.

Empowering the Organisation

The real power of AI emerges when it’s not a separate task, but part of how people work every day - AI is normal.

We’re already seeing it:

• Marketers tracking AEO (Answer Engine Optimisation) alongside SEO.

• Contact centres building their own service copilots tailored to their flow.

• Analysts skipping dashboards and just asking the question they need.

This is AI as a digital co-worker - useful, embedded, and quietly transformational.

And behind all of this? Technical teams making sure it’s stable, secure, compliant, value-driving, and scalable. We aren’t stepping away. We’re making the magic invisible - and that’s what unlocks safe scale.

Making AI Normal

We’re entering the Intelligence Era.

Not someday. Now. Our kids are native to this world already. For them, asking an AI is as normal as using a search bar. That same normalisation is coming to the workplace - and fast.

Just like Cloud, AI is becoming an expected part of every tool, every flow, every decision. That doesn’t make it simple. It makes it foundational.

And just like with Cloud, we need technology teams more than ever - to lead, to safeguard, to guide, and to empower. It’s our job to make this feel simple without making it simplistic, and then step out of the way of the business we have empowered.

What Good Looks Like

Good AI is invisible.

It’s there when you need it. It’s part of the work. It’s trustworthy, predictable, and boring in the best way.

You don’t need to “go use AI”. It’s just baked in. Like spellcheck. Like autocomplete. Like cloud sync. Like Instagram recommendations!

And one day, yes, we might not need AI strategy leads anymore 🤔. Not because we’ve lost relevance, but because we’ve won. Because it’s working.

Final Thought: The North Star

This is the shift:

From AI as experiment to AI as expectation. From labs and pilots to frontline productivity. From tech-led disruption to business-embedded value.

My North Star is simple:

Use AI wisely. Empower everyone. Make it normal, invisible - and make it work.

That’s how we lead in the Intelligence Era.

Photo by Fred Moon: Unsplash

Innovation is a barrier to success. I have seen, again and again, where Innovation is the main blocker to the successful delivery of business value. Here are some of my learning and recommendations on how to avoid Innovation to succeed.

Innovation is the catch-cry of the decade. Innovate or perish. But Innovation is often the focus area that kills a delivery project.

I am seeing Innovation (with a capital I) as a noose around otherwise sound delivery projects’ necks. This is Innovation as a Goal and it is a killer.

What are we talking about here?

Take a company I know. They have genuine Business Goals at risk, especially around falling Market Share. They need to mitigate these risks. With partially baked ideas as to why their share is falling they pull together a think tank of people from within the exec and business to ideate and envision the problem and design-think the solution.

And the problem? “We are not Innovative enough. Our customers want more Innovation. We need to Innovate. Innovation is the Goal!” So, what is the result? The project’s targets are things like SOA is the Goal, As-a-Service or Public Cloud is the Goal, Reuse is Goal. We have been dragged down to Technology ideals and things we understand. No sign of the real customer challenges we can add value too.

Okaaay... This is not the first time I have heard this type of thinking and I am sure you have too. Innovation is one of several placeholders for real Goals. I’ve even heard these within the same organisation, for the same project, from different areas of the same team.

I want to tell you that NONE of these innovative Technology approaches is the Goal. All of them are tools, with which to build solutions to mitigate risks to genuine Business Goals. They are not the Goal itself.

So, what happens when we substitute real Goals for a “panacea” technical solution? We lose sight of what we are trying to mitigate with the investment in the project. Why the project exists. Why we are investing the companies money in this work. The delivery of Business Value.

Once the real Goals are substituted by design tools or solutions, our decision making has lost its compass. The purpose is cloudy and the measure of success is vague.

We must Innovate! What is that, a mobile app, perhaps? Moving to the “cloud”? Online forms? Who knows without the Business Value Goal to guide us.

Do we really believe that a vague Goal like Innovation can fix everything? I consider it lazy thinking. What is the result, projects with vague solutions as the goal, at least the ones I have observed, will hit a wall with time or costs. At that point, scope starts to be tightened and the missing Business driver slips even further away from being delivered.

Don’t get me wrong here, lowercase i innovation is important - it is essential to lifting a good solution to a transformative one, but it must be in the right place. Innovation is a tool to meet your goals, not the goal itself. So, for me this, we must create converged conversations with the business. This is why I developed the 3D Investment Planning Process (I’ll talk more about this in another article) which will:

• Define: Really define the business problem - often the missing link and never done - and don’t forget to ask “Why?”.

• Develop: Now that we have the real dilemma to address for our business. We have the context within which to grab the toolkits of innovation, design thinking, envisioning, and technology evolutions to address and transform the real business value. Technology is now the Business Enabler!

• Deliver: Ensure that the Business Why remains at the centre of the planning, governance, and delivery teams’ thinking, and critically decision-making around project delivery.

Innovation, and the methodologies to create it, is an amazing thing but in the right context, and I have seen this in practice. It is NOT THE GOAL, the starting point, but a tool for moving from a good solution to a Business dilemma, to a transformation of Business thinking and value.

So, what do you think - do you agree? Should we ensure that Innovation is never the Goal? I am interested in your thoughts below.

Photo by Anton Shuvalov: Unsplash

If you have worked with me before you will know I ask “The Dumb Questions” - the questions we all assume we know the answers to.

My favourite question being, “Why?”.

I have found that a lot of the dilemmas we face in our transformation delivery can be traced back to assumed Whys - why we are doing it in the first place. Technology assumed the reason we were doing this was to save cost, Project Management assumed the reason was to deliver a level of ill-defined quality, and what Business wanted was something fast and good enough. You know the old adage around when we assume!

The Six-Sigma practice has been using Why as a means to troubleshoot root cause in their delivery methodology for a while now.

I use it to test the assumed solutions that we are choosing to deliver and the dilemma that they are targeted to solve.

Why this and why now? Is it the only solution, or the right solution - cannot tell if we do not understand the real dilemma we are wanting to resolve? Is it the right time - cannot tell this either without understanding the bigger picture of where things are and where they need to be?

A key challenge is when we don’t identify the real dilemma and see a “solution” as the Why.

I’ll explain.

Let me introduce you to our Business Owner - for some reason I want to call her Delilah. In this scenario, Technology is starting the transformation process well by creating converged conversations with our business customer and her clients. Delilah says, “My dilemma is I need a Mobile App.” Hallelujah, we have the Business Why and can work together to develop the solution.

Wrong, what has happened here is that Delilah - consciously, or unconsciously - has been struggling with the real Why and decided that a mobile app will be the right solution. So we are seeing one of her solutions as the Business Why and the actual dilemma is hidden from us. If we proceed with delivering this mobile app - we may well fix the problem, but probably not really deliver fully to the Business Why. Most importantly, Technology has not been able to add strategic business value to the conversation.

Here is where the Dumb Questions come in. Instead of accepting the Business Why, at face value, ask “Why?” Let’s continue our conversation with Delilah.

“Delilah, why do you need a mobile app?” What dilemma is the mobile app a solution to?

“Because people are mobile and don’t use our website.” So, do we have the Business Why, or is there another level to unpick?

“Why don’t they use the website?”

“Because it is too hard to use on their mobile.” Closer.

“Why is it too hard?”

“We’re getting a lot of abandoned applications; customers are telling us that the forms are hard to view and navigate, and don’t display well. “ That’s more like it.

“Ahh, I see. Thanks, Delilah. I think I can suggest some options to help with that.” Now I am addressing a real Business Dilemma.

Yes, absolutely a potentially drawn-out and expensive mobile app development project will likely deliver a working solution for Delilah, but so would a much smaller, cheaper, and faster redesign of the site to make the forms dynamic and workable on mobile browser platforms. There are more options and no one locked-in answer.

Yay for the “Dumb Questions”!

All of a sudden the assumptions and the trap of a single solution lock-in are gone. We have options. Technology is not solely a delivery function but has the opportunity to have a useful and converged conversation with the Business on what their options are and what value each can offer to resolve the Business’s real dilemma is.

Delilah now knows Why and is a more focused and happy partner with us.

Technology is the Business Enabler by asking “Why” - I like the sound of that.

What about you? Tell me about your experiences in the comments below.

Image by Arek Socha (qimono): Pixabay

How often do our technology projects seem to be derailed by the very customers we are delivering them to? Who is the villain in this piece? How can we change these tracks we are hurtling down and avoid a trainwreck?

This is how it usually starts, an idea or innovation from the technologists. “We can make things more awesome with [insert the latest tech here] and reduce costs.” Then the internal technology conversation goes further, “Let’s prioritise this transformation as it will be great for The Business in a few years when deployed. They’ll love it!”

Meanwhile, The Business has a separate internal conversation going on, “I need to put out these fires and stop this attrition, like yesterday! What can I do to change things up at speed? How do I change things up? What needs changing?”

Divergence

Two divergent - never overlapping - and separate conversations, from two very different viewpoints and universes. And in two very different languages - Business and Technology.

What is the end result? Is it a smooth convergence of goals and deliverables, or a derailed trainwreck? My experience shows it is often the latter - or at least disappointment and resentment on both sides.

Yet, there are no villains here. Everybody wants the best for the organisation, everybody sees their viewpoint as the way forward and is disappointed that the other group doesn’t understand.

This is the core challenge of using technology as the starting point. Technology is, and has always been, a service to support an outcome; the means, not the end; the solution, not the problem. In fact, it is only a part of a larger solution: People running Processes, supported by Technology. It is the last piece of the puzzle - how often do we put it first?

Reset with Why

How can we start the right conversation and ensure that it is a single aligned and converged one?

We need to wind back to the beginning - in fact to before the beginning - we need to understand the context.

We, technologists, need to ask and understand why we need a change. Simple enough, but as we have seen above, so often overlooked. I’m talking about The Business why, not The Technology why. So, we in technology need to align to and understand the business’s real challenges and needs. To do this we need to take the rare step of talking to The Business.

Reset, start a new set of conversations - this time between The Business and Technology. This reset can be kicked off by technology - it probably needs to be, initially, to show The Business why they should want to talk to us.

Talk with The Business accountable person about their challenges and needs - their Business Whys - the hurdles in the way of them meeting their Goals and Objectives. These often turn out to be challenges around people and processes. So can we ignore them because they are not technology? NO! Instead, we can rejoice! Technology is not the problem - we can now take our place as a supporting part of a real, needed solution to a known business problem.

Convergence

The reset conversation could look something like this, “Technology can support The Business’s people and process transformations with the introduction of Robotic Process Automation (RPA). Let me explain what RPA is and how it can help us all deliver the measurable business benefits and scale we need...”

A single, aligned, understood conversation across Business and Technology. A single set of goals and measurable benefits to realise - by everyone, together.

I have seen this in practice - it does take practise - and it does indeed deliver real aligned converged transformation.

Are you ready to reset your conversations and practice convergence? Have you experienced convergence, or perhaps divergence? I’d love to hear your story below.

Photo by Albin Berlin: Pexels

THE SYSTEM IS OUT TO GET YOU! On your path you will trip, you will fall. You will scream and curse. But, you will need to get back up and try again. You have no choice, it’s legislation - oh, and congratulations on the birth of Jenny - was it - your new baby!

What a way to introduce you to your parenting journey. A beautiful gift of disconnected bureaucracy wrapped up thoroughly in a bow of rampant Red Tape.

The Public Services is full of great people who want to do the best they can for the engine of their country. The challenges are the tools, policies and legislation they have to support them are 20th Century and not taking advantage of modern possibilities.

This bureaucracy is not intentionally malicious, disconnected, or targeting you. This bureaucracy is a result of siloed growth over a long time. This has produced a lack of end-to-end visibility, responsibility and delegated authority.

Historically, the engine of Government exists to serve government structures and support the implementation, running, and fulfilment of Legislation. It is focused on the needs of the system and still doing this with last century’s thinking about what is possible.

When you look at the engine of Government you see Agencies. When they act, they mostly act as individual agencies - that is what they are empowered to do.

The bureaucracy grew as and when required. A siloed, focused growth, by different groups over the decades. This has kept the short-term costs down, but left us with long-term pain and long-term national technology and bureaucracy debt. No understanding of the history of your need, no concept of predicting your future demand - you know I am over-simplifying for effect here!

What would it be like if it focused on us?

Imagine the engine of Government understanding what you need. Imagine the engine of Government proactively sorting things for you. Imagine the engine of Government making it easy for you to get what you need.

Imagine the engine of Government understanding what you need.

“Congratulations on the birth of baby Jenny. This is how we can help. We’ve already done all this and just need to hear from you on that, from there we can present you with the other!

Oh, and by the way, this is everything you need to be doing for now - simple and all in one place. Again, Congratulations!”

In the past, the system did not have the tools to cost-effectively personalise our engagement. Thus, I need to remember, I get penalised when I forget, and I have to work out the combination of agencies to talk to for each transaction. I don’t know about you, but that’s not a lot of fun.

I am more than just a number, more than a series of disconnected transactions within the engine of Government. We don’t need to run things like this anymore - we have the power to upgrade the system’s engine!

What would it be like if it understood your situation?

Imagine the engine of Government understanding your situation. Imagine the engine of Government remembering you. Imagine the engine of Government proactively sorting things out for you.

“Hello again, Jenny is turning four soon, Happy Birthday! We’d like to help her begin her life of learning with…”

“Jenny has her restricted license now. Here are some interesting services in your area that she could use to assist with the next step on her driving journey.”

“Hi, Jenny, I’m a Bot, and here to help. So you’d like a passport, that is a straightforward process, let me help you. We can pre-populate a lot of the information needed from information in your driver’s license data. I just need your permission to gather this…”

You are more than just a number.

The Road Ahead with AI

Yes, there is history and legacy to deal with and this will not happen overnight, but there is motivation in the halls of government, and now cost-effective technical capabilities, to change things up. Public Servants are citizens too.

The evolution of our engagement with social networks has shown us what should be possible in our interactions with the Government and we want more. We can be engaged with by institutions in a personalised way. You can be seen, understood, and approached as a joined-up person rather than a series of transactions or unrelated collections of data in individual agencies.

We’ve seen that the tools are in place to make this real, big data sets, AI, and the enabling Cloud platforms give us:

• The ability to safely join up the masses of information to allow a citizen to engage with Government in a way that makes sense to the citizen, while still supporting the agency needs.

• The intelligence to simplify things - across agency boundaries - for each individual citizen, to see us as a person, and allow agencies to be proactive in their support.

• The cloud platform computing power and storage capacity necessary for the AI to support this.

It’s more than a Tech change

This engagement evolution is a collaboration, an expansion, a new empowering of our human Public Service and us citizens - it is NOT an abdication or substitute. And we in technology must support this.

The engine of Government can be upgraded. This engagement evolution effort needs more than a technology upgrade. We are removing bureaucracy debt as well as technology debt. It must include:

• Change in thinking (citizen at the heart and there is value to us to be seen as joined up),

• Change in policy (seeing us as whole individuals - welcome to the cross-agency platform era),

• The resulting change in legislation (enabling the safe citizen-centric joined up engagement across agencies).

These make up the real evolution - the tech is just an enabler. And there are real and imagined risks in the change.

The news has shown us that AI, Cloud platforms, and big data sets used in isolation of policy leads to abuse - intentional or otherwise.

We need to talk. To have a conversation and, as a nation, agree on frameworks for how this upgrade can be done ethically, transparently, and with accountability (Microsoft has started this conversation in the free books The Future Computed and A Cloud for Global Good)

This is a conversation for all of us - I’m having it with Public Servants and citizens daily these days. There is a way forward, the capabilities are real today.

Let’s get this conversation started - tell me in the comments, do you agree? Whether you agree or disagree with what I am saying, we need to talk.

The System can be humanised and the path to travel made safe, smooth and straight for us to walk - safe enough for baby Jenny.

Image by Gerd Altmann: Pixabay