Build, buy, or wait: A leader's guide to digital strategy under uncertainty
Technology choices are often made under pressure - pressure to modernize, to respond to shifting client expectations, to demonstrate progress, or to keep pace with rapid advances in AI. In those moments, even experienced leadership teams can fall into familiar traps: over-estimating how differentiated a capability will remain, under-estimating the organizational cost of sustaining it, and committing earlier than the strategy or operating model can realistically support.
After decades of working with leaders through digital and technology-enabled transformations, I’ve seen these dynamics play out again and again. The issue is rarely the quality of the technology itself. It’s the timing of commitment, and how quickly an early decision hardens into something far harder to unwind than anyone intended.
What has changed in today’s AI-accelerated environment is not the nature of these traps, but the margin for error. It has narrowed dramatically.
For small and mid-sized organizations, the consequences are immediate. You don't have specialist teams running parallel experiments or long runways to course correct. A single bad platform decision can absorb scarce capital, distort operating models, and take years to unwind just as the market shifts again.
AI intensified this tension. It is wildly over-hyped as a silver bullet and quietly under-estimated as a structural disruptor. Both positions are dangerous. AI won’t magically fix broken processes or weak strategy, but it will change the economics of how work gets done and where value accrues.
When leaders ask how to approach digital platforms, AI adoption, or operating model design, four questions consistently matter more than the technology itself.
- What specific market problem does this solve, and what is it worth?
- Is this capability genuinely unique, or is it rapidly becoming commoditized?
- What is the true total cost - not just to build, but to run and evolve over time?
- What is the current pace of innovation for this niche?
For many leadership teams, answering these questions leads to the same strategic posture. Move quickly today while preserving options for tomorrow. Not as doctrine, but as a way of staying adaptive without mistaking early commitment for strategic clarity.
Why build versus buy is the wrong starting point
One of the most common traps organizations fall into is treating digital strategy as a series of isolated build-vs-buy decisions. That framing is too narrow, and it usually arrives too late.
A more powerful question is this. How do we preserve optionality as the landscape continues to evolve? Technology decisions often become a proxy for deeper organizational challenges. Following acquisitions or periods of rapid change, pressure frequently surfaces at the front line. Sales teams respond to client feedback. Delivery teams push for speed. Leaders look for visible progress.
In these moments, technology becomes the focal point for action. Not because it is the root problem, but because it is tangible.
The real risk emerges operationally. Poorly sequenced transitions, disruption to the core business, and value that proves smaller or shorter-lived than anticipated. Teams become locked into delivery paths that no longer make commercial sense, while underlying system assumptions remain unchanged.
The issue is rarely technical. It is temporal.
Optimizing for short-term optics, particularly client-facing signals of progress, often comes at the expense of longer-term adaptability. A cleaner interface over an ageing platform may buy temporary parity, but it can also delay the more important work of rethinking what is possible in the near and medium term.
Conservatism often shows up quietly here. Not as risk aversion, but as a preference for extending the familiar rather than exploring what could fundamentally change.
Licensing as a way to buy time and insight
In fast-moving areas such as AI orchestration, many organizations are choosing to license capability rather than build it internally. This is not because licensing is perfect. It rarely is. It introduces constraints and trade-offs. But it was fast. And more importantly, it acknowledged reality.
The pace of change in this space is such that what looks like a good architectural decision today may be actively unhelpful in twelve months. Licensing allowed us to operate right at the edge of what we actually understood at the time - without pretending we knew where the market would land six or twelve months later.
Licensing should not be seen as a lack of ambition. It is often a way of buying time, learning cheaply, and avoiding premature commitment. Building too early doesn’t make you visionary, often it just makes you rigid.
AI is neither a silver bullet nor a feature
Coaching is a useful microcosm of the broader AI debate.
Great AI coaching that is designed with intent and grounded in real coaching methodology can genuinely augment the experience and extend impact. The market is saturated with AI-enabled coaching tools and what is especially disappointing is that many are thin layers of prompts wrapped around a large language model. They are responsive, polite, and superficially impressive - and they largely miss the point.
Effective coaching isn’t about constant responsiveness. It’s about clarity. It’s about bringing experience, structure, credibility, and connection to moments where someone is stuck.
At the other extreme, coaches themselves are often deeply traditional. A heavy pen, a leather-bound notebook, and a Royal Copenhagen mug of coffee are far more likely to be sitting on the desk than the latest GPT or Gemini model.
That conservatism is understandable - coaching is built on trust, presence, and human connection - but it’s increasingly misaligned with how scale and impact are actually created.
The real opportunity for AI is not to replace human work with a chat interface. It is to codify what actually works. The decision points, frameworks, insights, and moments that drive behavior change. AI can then be used to augment and extend that value at scale.
A polished interface over generic capability is not enough. If AI does not strengthen the core value of the work, it is theatre, not transformation.
What this means for leaders
Across all of these examples, the same pattern shows up.
The hardest decisions are rarely about capability, they are about timing, alignment, and conviction.
Building from scratch only makes sense when you can clearly articulate:
- What you believe that the market does not
- Why that belief creates defensible value
- Why you’re willing to concentrate risk behind it
Clear vision scales extraordinarily well when it’s tightly held. The success of narrow, focused Silicon Valley start-ups is testament to that.
Larger organizations often carry a broader set of commitments. That complexity increases when depth of expertise is spread across functions, and even more so when sales teams have significant autonomy at the point of sale. Alignment becomes harder not because people are wrong, but because too many partial truths are competing at once.
In these environments, strategic clarity, not headcount or spend, creates advantage.
This is why many leadership teams choose to license early. Not because building is wrong, but because most organizations have not yet earned the right to build.
Related content
Three decisions that changed everything.
Two years ago, we made three deliberate decisions about how BTS would move with Applied AI.
We would become our own Customer Zero.
While others were building strategies, defining governance, and waiting for clarity, we made a different call: we decided not to wait. Not because the stakes were low, but because they were high. And because in a space evolving this quickly, clarity wouldn’t come from planning. It would come from movement.
So instead of starting with a roadmap, we started with three principles:
- No top-down mandate. The people closest to the work figure it out.
- IT must evolve from gatekeeper to enabler - leading AI trials and fast experimentation.
- Don’t wait for certainty.
We set the organization in motion, and once we did, things started to move quickly.
What if we started this company today?
Waiting for certainty is itself a choice, and it’s costing companies more than they realize.
We started where we knew the work best: our simulations. No perfect plan, just teams moving, trying, and iterating.
Simulations are core to who we are at BTS. Companies that simulate don’t just make better decisions; they execute faster and build more engaged cultures.
The team asked a simple question:
"What if we were to start our company today?”
That question started the flywheel.
They asked IT for a few licenses and started building - vibe-coding, writing agents, and testing tools - moving at a pace that would make any VC-backed start-up smile.
The messy middle.
At first, the team was underwhelmed.
The early reports were blunt:
“Not good with math.”
“Poor graph capabilities.”
The team wasn't discouraged. They kept tinkering - jumping between tools, staying on top of new releases, experimenting constantly.
This was a small team, across 24 countries, building off each other’s ideas. Laughing at crazy creations. Breaking things. Iterating in a sandbox alongside real clientwork.
Each cycle produced something:
- A sharper scenario
- A faster build
- A more powerful simulation
The flywheel was turning, and it was generating something real.
When the diamond appeared.
Then something shifted.
The team moved into client trials across five countries. They figured out ISO compliance and built the architecture to handle the complexity, the “spaghetti.”
And what emerged wasn’t incremental:
- What used to take weeks started happening in days.
- Limited creativity started to feel like unlimited innovation.
- Clients became self-serving.
- Agentic simulations were built directly into client systems for real-time updates and preparation.
This was our first AI diamond - a high-impact outcome created by many cycles of experimentation compounding into real value.
It only appeared because we kept the flywheel turning, each cycle increasing the odds that something would break through.
95% adoption in eight weeks.
Then it was time to take the AI diamond global.
BTS is decentralized and highly entrepreneurial. We operate across 24 countries and 38 offices, where local teams have real autonomy.
And historically? That’s meant a low appetite for adopting something built somewhere else and pushed from the center.
So we expected resistance.
Instead, something surprising happened.
In the first eight weeks, we saw 95% adoption across our global footprint.
It felt completely different from our own digital initiatives, ERP implementations, top-down rollouts of the past.
This moved on its own. Why?
We realized it didn’t start with a framework or a model, it started with a feeling.
The feeling of being at the leading edge of one’s craft and profession.
- Joy
- Excitement
- Pride
As we watched this play out across teams it stopped feeling like isolated wins.
There was a pattern to it. A repeatable, organic, innovation motion.
And the flywheel didn’t stop with simulations.
It spread across finance, sales enablement, legal, operations, and client delivery. Some cycles led to small improvements, and others revealed new diamonds.
Not becausewe planned for them, but because we built the conditions for people to find them.
The question I'd ask any CEO right now: Is your flywheel turning, or are you still waiting for the perfect plan?
In part 2, I’ll share the key success factors behind the breakthrough, and what we’re now seeing across more than 120 global clients.
Today’s customers are more informed, more selective, and more time-poor. They need conversations that help them prioritize, decide, and move forward.
And yet, 58% of sales meetings fail to create real value.
Not because sellers lack capability, but because conversations are not designed to move decisions forward.
“Customers don’t act on every need they recognize.
They act when something becomes a priority.”
In this short executive brief, you’ll discover
- Why most conversations inform… but don’t drive action
- What actually makes customers prioritize and move
- How to create urgency without damaging trust
- The shift from presenting solutions to enabling decisions
- What separates conversations that stall from those that accelerate momentum
If your teams are experiencing stalled deals, delayed decisions, or slow pipeline movement, this brief will help you understand why, and what to do differently.
For more than a decade, Agile has played a central role in modernizing organizations. It improved collaboration, accelerated delivery cycles, and reshaped how teams build products and services.
However, Agile was never the final destination.
Scaling ceremonies does not redesign an organization. Implementing frameworks does not guarantee strategic adaptability. And in a world defined by exponential technological acceleration and artificial intelligence, improving execution alone is no longer sufficient.
Today, competitive advantage depends on something deeper: the ability to continuously adapt while still delivering value to customers.
This capability is known as Enterprise Agility.
Enterprise Agility as an organizational capability
Enterprise Agility is often misunderstood as a methodology or framework. In reality, it represents something far more fundamental.
It is the capability of an organization to generate sustainable value in uncertain environments through continuous adaptation of strategy, operating models, and culture.
Organizations with this capability are able to:
- Continuously prioritize the initiatives that generate the greatest impact
- Make faster and better-aligned decisions
- Reconfigure structures without major disruption
- Learn systematically from customers and market signals
- Integrate strategy and execution into a unified operating flow
When this capability becomes embedded within the organization rather than dependent on isolated initiatives, companies evolve into Adaptive Organizations.
But this evolution does not happen automatically. It requires activating structural change mechanisms across the enterprise.
The five levers that enable Enterprise Transformation
Enterprise Transformation is not about implementing Agile practices across teams. It is about building the capabilities required to sustain continuous adaptation.
Five structural levers play a critical role in enabling this transformation.
1. From methods to organizational design
For years, the conversation around agility focused on which framework to implement: Scrum, SAFe, LeSS, or Kanban.
Today, the more relevant question is different:
Is the organization designed to generate a continuous flow of value?
This shift requires moving beyond project-based structures toward operating models built around products, capabilities, and value streams.
Organizations must reduce structural friction and integrate strategy, execution, and learning into a single system.
Without this redesign, agility often remains superficial.
2. From rigid planning to continuous prioritization
Traditional annual planning cycles were designed for stable environments.
In today’s context, adaptive organizations manage dynamic portfolios and adjust priorities continuously based on real-time information.
Planning becomes an ongoing process rather than a yearly event.
Competitive advantage no longer comes from predicting the future better, it comes from the ability to adjust when the future changes.
3. From misaligned autonomy to distributed strategic coherence
Decentralization without alignment creates chaos. Excessive centralization creates slow decision-making.
Adaptive organizations balance these forces by enabling distributed decision-making within clear strategic guardrails.
Transparency, alignment, and shared accountability ensure that teams operate autonomously while remaining connected to the broader strategic direction.
4. From operational efficiency to accelerated learning
In the age of artificial intelligence, the speed of learning becomes more important than the speed of execution.
Organizations must build the ability to:
- Detect market signals early
- Understand strategic implications
- Experiment at low cost
- Learn systematically
- Adjust quickly
Artificial intelligence acts as a cognitive amplifier within this cycle, improving decision quality and enabling faster experimentation.
The objective is not simply to automate work, but to accelerate the organization’s adaptive capacity.
5. From change as a project to permanent adaptation
Many transformation initiatives fail because they are treated as temporary programs.
But adaptation is not a project, it is a strategic capability.
Organizations must integrate change into their daily operations by developing leadership capabilities, building adaptive cultures, and measuring real impact rather than superficial adoption metrics.
Transformation becomes a structural characteristic of the organization rather than an extraordinary initiative.
The real meaning of Enterprise Transformation
Agile was the first step, but it was never the destination.
Enterprise Transformation exists to build Enterprise Agility. And Enterprise Agility enables organizations to become truly adaptive.
In an environment where artificial intelligence accelerates innovation and lowers barriers to entry, stability is no longer a protection. Rigidity becomes a liability.
The critical question for organizations today is not whether they execute their plans efficiently.
It is whether they can change those plans faster than their competitors.
To understand how Enterprise Transformation can help your organization build this capability, discover more at Netmind a BTS company
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Organizations have long wanted to scale coaching, but have been limited by cost and capacity. With AI, that's beginning to change as new platforms make coaching more accessible, flexible, and available on demand, extending support beyond a select group of leaders to entire populations.
For talent leaders, this shift creates both opportunity and complexity. With greater reach comes a new set of trade-offs: how to balance access with depth, flexibility with accountability, and efficiency with meaningful development.
The limits of unlimited (coaching).
Unlimited coaching sounds like the obvious answer. Remove the barriers, give everyone access, let people engage on their own terms. What's not to like?
In practice, quite a bit.
When coaching has no defined structure or cadence, engagement tends to become episodic - people show up when something feels urgent and step back when it doesn't. The coaching relationship never quite deepens. Conversations cover ground but don't build on it. And the development that was supposed to happen keeps getting pushed to the next session, and the next.
Three patterns emerge:
- Sporadic engagement over sustained development. Without a rhythm to anchor the work, coaching becomes reactive. Clients bring whatever is most pressing that week rather than working toward something larger. Progress happens in bursts, if at all.
- Insights that don't compound. Great coaching reveals patterns over time - things a client can't see in one session but can't unsee after several. Without continuity, and without a consistent coaching relationship to hold the thread, each conversation starts close to zero.
- Outcomes that are hard to measure. No milestones. No defined endpoint. No clear way for the organization, or the client, to know whether it's working. Activity fills the gap where impact should be.
The result is a model that's easy to scale and hard to defend. Which is exactly the problem talent leaders are navigating right now.
The relationship is the lever.
Decades of research into what makes coaching work keeps arriving at the same answer: it's the relationship. Not the platform, not the methodology. The relationship.
When a coach and client build trust over time, developing shared language, and returning to the same themes with increasing depth, something shifts. Conversations get more honest. Insights stick. The client starts doing the work between sessions, not just during them. That's when coaching becomes genuinely transformative, and it can't be rushed or replicated in a one-off session.
The ICF and EMCC are clear on this: continuity is what dives outcomes. The coaching engagements that produce lasting change are the ones where each session builds on the last, not the ones that simply offer more access.
Three principles make that possible: Consistency, Continuity, and Completion.
1. Consistency
The foundation everything else is built on.
The temptation when designing a coaching program is to treat flexibility as a feature - let people book when they want, swap coaches freely, engage on their own schedule. But frequent coach changes reset the clock. Every new coach has to earn trust, learn context, and find their footing with the client. That's time spent getting started, not getting somewhere.
A stable coaching relationship works differently:
- The coach starts to see around corners, uncovering patterns the client can't see on their own
- The client stops performing and starts being honest
- The relationship itself becomes a source of accountability, not just the sessions
Consistency doesn't constrain the work. It's what makes the deeper work possible.
2. Continuity
What turns a series of sessions into genuine development.
Without continuity, coaching tends to be additive at best- each session offers something useful, but nothing compounds. With it, the work builds on itself in ways that can't happen in isolated conversations.
What continuity makes possible:
- A limiting belief surfaced in session three becomes a thread that runs through the rest of the engagement
- A behavioral pattern the client couldn't see at the start becomes impossible to ignore by the end
- Space opens up for the harder work - the kind that requires sitting with discomfort across multiple sessions, not resolving it quickly and moving on
That slower, deeper work is where lasting change actually happens. It doesn't come from more sessions. It comes from the right sessions, in the right order, with the same person.
3. Completion
The most underrated principle of the three.
In a world of unlimited access, there's no finish line, and without one, it's surprisingly hard to know what you're working toward, or whether you've gotten there. A defined endpoint changes the entire shape of an engagement.
A clear endpoint creates urgency and focuses every session on what matters most.
- Shifts the question from "what should we talk about this week?" to "what do we need to accomplish before we're done?"
- Gives both coach and client a body of work to look back on, not just a log of conversations
For talent leaders, this is also what makes coaching legible as an investment. Sessions logged is an activity metric. A cohort of leaders who completed a structured engagement and can articulate what changed, that's a result.
Don't just scale it, design it (here’s how)
The opportunity in front of talent leaders right now is significant. The organizations that will get the most from this moment are the ones that treat coaching design as seriously as coaching delivery.
Practical design decisions:
- Define the arc before you launch: set the number of sessions, the cadence, and the goals upfront, not after people have already started booking
- Protect the coaching relationship: Make coach switching the exception, not the default, and design your program to discourage unnecessary re-matches
- Build in milestones: create structured check-ins at the midpoint and end of each engagement so progress is visible to both the coach and the organization
- Separate on-demand support from developmental coaching: Use AI-enabled tools for in-the-moment guidance, and reserve structured engagements for the deeper work
- Measure completion, not just activation: Track how many people finish an engagement, not just how many start one
Questions to pressure-test your design:
- Does every participant know what they're working toward before their first session?
- Can your coaches see enough context about a client's journey to pick up where they left off?
- Would you be able to show, at the end of a cohort, what changed, and for whom?
Access opened the door. Intention is what makes it worth walking through.
Three decisions that changed everything.
Two years ago, we made three deliberate decisions about how BTS would move with Applied AI.
We would become our own Customer Zero.
While others were building strategies, defining governance, and waiting for clarity, we made a different call: we decided not to wait. Not because the stakes were low, but because they were high. And because in a space evolving this quickly, clarity wouldn’t come from planning. It would come from movement.
So instead of starting with a roadmap, we started with three principles:
- No top-down mandate. The people closest to the work figure it out.
- IT must evolve from gatekeeper to enabler - leading AI trials and fast experimentation.
- Don’t wait for certainty.
We set the organization in motion, and once we did, things started to move quickly.
What if we started this company today?
Waiting for certainty is itself a choice, and it’s costing companies more than they realize.
We started where we knew the work best: our simulations. No perfect plan, just teams moving, trying, and iterating.
Simulations are core to who we are at BTS. Companies that simulate don’t just make better decisions; they execute faster and build more engaged cultures.
The team asked a simple question:
"What if we were to start our company today?”
That question started the flywheel.
They asked IT for a few licenses and started building - vibe-coding, writing agents, and testing tools - moving at a pace that would make any VC-backed start-up smile.
The messy middle.
At first, the team was underwhelmed.
The early reports were blunt:
“Not good with math.”
“Poor graph capabilities.”
The team wasn't discouraged. They kept tinkering - jumping between tools, staying on top of new releases, experimenting constantly.
This was a small team, across 24 countries, building off each other’s ideas. Laughing at crazy creations. Breaking things. Iterating in a sandbox alongside real clientwork.
Each cycle produced something:
- A sharper scenario
- A faster build
- A more powerful simulation
The flywheel was turning, and it was generating something real.
When the diamond appeared.
Then something shifted.
The team moved into client trials across five countries. They figured out ISO compliance and built the architecture to handle the complexity, the “spaghetti.”
And what emerged wasn’t incremental:
- What used to take weeks started happening in days.
- Limited creativity started to feel like unlimited innovation.
- Clients became self-serving.
- Agentic simulations were built directly into client systems for real-time updates and preparation.
This was our first AI diamond - a high-impact outcome created by many cycles of experimentation compounding into real value.
It only appeared because we kept the flywheel turning, each cycle increasing the odds that something would break through.
95% adoption in eight weeks.
Then it was time to take the AI diamond global.
BTS is decentralized and highly entrepreneurial. We operate across 24 countries and 38 offices, where local teams have real autonomy.
And historically? That’s meant a low appetite for adopting something built somewhere else and pushed from the center.
So we expected resistance.
Instead, something surprising happened.
In the first eight weeks, we saw 95% adoption across our global footprint.
It felt completely different from our own digital initiatives, ERP implementations, top-down rollouts of the past.
This moved on its own. Why?
We realized it didn’t start with a framework or a model, it started with a feeling.
The feeling of being at the leading edge of one’s craft and profession.
- Joy
- Excitement
- Pride
As we watched this play out across teams it stopped feeling like isolated wins.
There was a pattern to it. A repeatable, organic, innovation motion.
And the flywheel didn’t stop with simulations.
It spread across finance, sales enablement, legal, operations, and client delivery. Some cycles led to small improvements, and others revealed new diamonds.
Not becausewe planned for them, but because we built the conditions for people to find them.
The question I'd ask any CEO right now: Is your flywheel turning, or are you still waiting for the perfect plan?
In part 2, I’ll share the key success factors behind the breakthrough, and what we’re now seeing across more than 120 global clients.
La maggior parte delle riunioni di vendita non fallisce.
Semplicemente non porta a una decisione.
Ed è lì che si perde valore.
I clienti di oggi sono più informati, più selettivi e hanno meno tempo.
Non hanno bisogno di altre presentazioni di prodotto.
Hanno bisogno di conversazioni che li aiutino a stabilire le priorità, decidere e andare avanti.
Eppure, il 58% delle riunioni di vendita non riesce a creare valore reale.
Non perché i venditori manchino di capacità, ma perché le conversazioni non sono progettate per far avanzare le decisioni.
“I clienti non agiscono su ogni esigenza che riconoscono.
Agiscono quando qualcosa diventa una priorità.”
In questo breve executive brief scoprirai:
- Perché la maggior parte delle conversazioni informa… ma non porta all’azione
- Cosa spinge davvero i clienti a stabilire priorità e muoversi
- Come creare urgenza senza compromettere la fiducia
- Il passaggio dal presentare soluzioni al facilitare decisioni
- Cosa distingue le conversazioni che si bloccano da quelle che accelerano il progresso
Se i tuoi team stanno affrontando trattative bloccate, decisioni ritardate o un pipeline lento, questo brief ti aiuterà a capire il perché e cosa fare in modo diverso.
Scarica l’executive brief e scopri come progettare conversazioni che portano davvero a decisioni.