Does Your Organization Have an AI Strategy?
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By Esteve Almirall, Professor at the Department of Operations, Innovation and Data Sciences at Esade and author of “Qué hacer cuando todo cambia”
There is little doubt today that artificial intelligence is transforming not only how organizations operate, but also how they compete—and even reshaping the very structure of competition itself. Intelligent agents are becoming integral to this shift, augmenting and automating tasks in customer service, sales, compliance, onboarding, and even legal work.
What lies ahead, however, is more than just another technological wave focused on efficiency. This time, AI is poised to reconfigure markets, logistics, research, and operations at their core.
The Strategic Blind Spot
The challenge for leaders is that we are still at the early stages of this transformation. Best practices are scarce, roadmaps are incomplete, and the cost of missteps—in timing, tools, or approach—can be very high.
Yes, your organization needs an AI strategy. The real question is: how do you develop a strategy when the disruption itself is still unfolding?
At its essence, AI is expanding the frontier of what is technologically possible. Tasks we already perform can now be done differently, faster, or better. Entirely new tasks—previously unimaginable—are now feasible. For organizations, this dual expansion presents an opportunity to unlock new levels of competitiveness.
But the reverse is also true. As a general-purpose technology, AI will eventually permeate every industry. Markets will shift, cost structures will change, and customer expectations will evolve. Not adopting is not an option—just as no business today could survive without the internet, mobile phones, or apps.
Ultimately, there will be only two types of organizations: those that adopt AI, and those that don’t survive.
AI Adoption’s Speed Dilemma
If adoption is unavoidable, the critical question becomes: at what speed?
It is tempting to believe adoption should move at the pace of technology. The hype cycle, constant media coverage, and relentless vendor pitches reinforce this idea. But history shows that adoption follows many speeds, depending on context.
Consider: nearly every student today uses ChatGPT or similar tools, yet organizational adoption remains limited, and government adoption even less so. Hospitals in China are racing to integrate AI, while in Europe, uptake is more cautious, even resistant. Competitive intensity, cultural norms, regulatory environments, organizational inertia, and barriers to entry all shape the pace of adoption.
This complexity makes AI strategy even harder to design. Companies must move fast enough to capture opportunities while adapting their approach to local realities.
Three Paths To AI Adoption
Adoption, however, is not a single step—it comes in very different forms. Broadly speaking, organizations will experience shadow adoption, tool adoption, and transformative adoption. Each carries distinct implications.
1. Shadow Adoption
This is already happening inside your organization, often without your knowledge. According to a University of Melbourne and KPMG research from this year, nearly three in five employees (58%) intentionally use AI at work on a regular basis. They use AI to summarize documents, improve writing, translate texts, build spreadsheets, generate reports, design diagrams, and create slide decks.
The barriers to entry are nonexistent, the benefits obvious. Trying to prohibit this is futile—it only drives usage underground, erodes trust, and risks cultural misalignment being ultimately corrosive. Instead, organizations should acknowledge shadow adoption, empower and guide it learning from how employees are already benefiting.
2. Tool Adoption
The next stage is formalizing AI use. Organizations select approved tools, provide training, incentivize usage, and embed systems like ChatGPT, Manus, Claude, or domain-specific platforms into workflows. This stage boosts productivity, quality, and focus, often measurably so.
Yet here lies a paradox: while individual productivity improves, these gains do not always show up in company-level performance metrics. Why? Because efficiency in small tasks rarely transforms entire processes. The uplift is real but incremental.
Although tool adoption delivers clear benefits, it also carries risks. In dynamic, elastic markets, incremental productivity gains from tool adoption often translate into greater competitiveness and even short-term market share growth. This creates incentives to expand headcount or overinvest in workflow optimization. The trend is amplified when companies adopt workflow automation platforms like Make or Zapier.
The danger is that these approaches can lock organizations into augmentation improvements, real but far from what is achievable. The real multiplier effect comes not from augmentation or piecemeal workflow automation, but from full automation. Without pursuing deeper transformation, organizations risk missing the structural benefits that only automation can deliver.
3. Transformative Adoption
True competitive advantage comes from transformative adoption. This means rethinking not just tools but structures, processes, and business models. It shifts from augmentation to automation, from improving today’s work to reinventing tomorrow’s organization.
Take compliance, customer service, or bank reconciliation. These can be marginally improved with workflow tools—or radically reinvented through full automation. The latter unlocks orders of magnitude more value and scalability but requires organizational redesign, power shifts, new governance and exploration.
Transformative adoption is not easy. It is disruptive, politically sensitive, and often resisted within established organizations—which is why startups are usually the ones to lead it. Yet despite the challenges, it remains the only path that ensures not just survival, but long-term growth. Tool adoption can buy time; transformative adoption builds the future.
From Strategy to Action
So where does this leave leaders?
- Acknowledge Shadow Adoption – Don’t fight it. Learn from it.
- Enable Tool Adoption – Provide structure, training, and governance.
- Pursue Transformative Adoption – Use AI not only to improve efficiency but to reimagine your organization.
The lesson from past general-purpose technologies is clear: those who delay or limit adoption fall behind. The internet, mobile, and cloud left no survivors among non-adopters. Generative AI will be no different.
The choice for leaders is stark: treat AI as a marginal tool or embrace it as the foundation of a new organizational strategy. The first path leads to incremental gains—and eventual mediocrity and obsolescence. The second path leads to reinvention and resilience.
Which will your organization choose?
