How CEOs and Large Enterprises can Unlock the Power of AI
As AI moves from experimentation to enterprise-wide adoption, a divide is emerging between organisations that simply deploy tools and those that rethink how value is created in an AI-enabled world.
Success is increasingly shaped by mindset, culture and the willingness to embed AI into everyday decision-making rather than treating it as a standalone initiative.
Here, Ali Alkhafaji, who recently became CEO at Apply Digital after serving as CAIO at Omnicom, explores what truly separates AI leaders from laggards and how organisations can balance ambition with execution.
What currently separates AI leaders from laggards?
The gap isn't access to technology, it's the quality of the question being asked. Laggards ask "how do we use AI to do what we already do faster?" Leaders ask "given what AI makes possible, what should we be doing that we couldn't do before?" That reframing changes everything downstream: the problems you prioritise, the talent you hire, the partnerships you pursue and the metrics you hold yourself accountable to.
The second separator is organisational courage. Most companies have now run AI pilots. The laggards treat those pilots as endpoints, proof of concept that gets filed away. Leaders treat them as the starting point for reimagining how value is created and delivered. They're willing to disrupt their own models before someone else does.
The third is cultural curiosity. The organisations pulling ahead aren't just the ones with the biggest AI budgets, they're the ones where genuine curiosity about what's next runs through the team, not just the leadership. That means people who read market signals early, ask hard questions about where the technology is heading and connect those answers back to how the business should evolve. Curiosity at a cultural level creates a compounding advantage: teams that have been actively experimenting, questioning and learning for three or four years aren't just ahead technically, they're ahead intellectually and strategically. That kind of lead is far harder to close than any technology gap.
What mindset shift do you feel CEOs still need to make about AI?
The most persistent misconception I encounter is treating AI adoption as a project rather than a posture. CEOs commission AI initiatives, appoint AI leads and measure deployment percentages, then wonder why the needle isn't moving. The problem is that adoption requires the whole organisation to change how it thinks, not just how it operates. If you don’t use AI as a CEO 50-100 times a day then your team will not either.
The shift that matters is from AI as a tool you deploy to AI as a capability you build into how your people work every day. That means investing seriously in enablement and change management, not as afterthoughts to a technology rollout, but as the primary programme. The technology is the easy part. Helping a 10,000-person organisation develop new instincts about when to trust AI, when to challenge it and how to collaborate with it effectively is a genuine leadership challenge, and most CEOs are underinvesting in it. This is a new muscle that we all need to develop.
The other shift is urgency without panic. There's a version of AI leadership that's performative, moving fast to signal innovation without the depth to sustain it. The CEOs who will look back proudly on this period are the ones who built genuine capability, not the ones who announced the most initiatives.
How can companies balance long-term AI bets with short-term results?
The short-term bet is clear: infuse AI and agentic workflows into the customer experience work we're already doing. That's where clients feel the impact immediately, faster content, smarter personalisation, more responsive digital products. It's demonstrable, it builds confidence and it funds the next conversation.
The longer-term bet is more structural. We're building toward a model of forward-deployed AI consultants, practitioners who embed directly inside client organisations, not to deliver a project and leave, but to build capability from the inside out. Paired with that is an investment in repeatable, industry-specific solutions grounded in the verticals we've chosen to master. Generic AI consulting is already becoming a commodity. The durable advantage sits in knowing CPG, sports and entertainment, B2B manufacturing or healthcare deeply enough that your AI solutions carry genuine domain intelligence, not just technical competence applied to a brief.
The two bets reinforce each other. The near-term CX work generates the client relationships, the real-world data and the credibility that make the longer-term model possible. You can't walk into a boardroom and pitch forward-deployed AI transformation without a track record of delivery. We're building both in parallel, deliberately.
If AI is a democratiser, how should enterprises unlock it across the organisation?
AI is the ultimate democratiser of size. For the first time, a 10-person team with the right enablement and the right tools can operate with the reach and output of an organisation ten times larger. That's genuinely new, and it cuts both ways.
For large enterprises, the implication is uncomfortable: scale, which has historically been a moat, is no longer sufficient protection. A nimble competitor with deep AI fluency can close gaps that would have taken a decade to close before. 2026 may well be the year of the one-person unicorn, and that should concentrate the mind of every enterprise leadership team.
The path forward for large organisations isn't to chase speed by pushing AI tools out to everyone at once. It's to build genuine fluency through structured training and enablement, identify the pockets of the organisation where AI amplification creates the most leverage, and remove the cultural and process friction that stops people from actually changing how they work. The technology is available to everyone. The organisations that unlock it will be the ones that treat workforce transformation as the primary investment, not the support track for a technology deployment.