Everyone's buying AI tools. Almost nobody knows how to make them work.
The numbers tell a story most executives don't want to hear. Seventy-four percent of organizations struggle to move beyond proofs of concept and generate tangible value from their AI investments. Only 26% have developed the capabilities needed to scale AI beyond experimentation.
We're watching the largest execution gap in modern technology adoption.
Companies race to adopt AI, driven by competitive pressure and market hype. They invest in platforms, hire data scientists, launch pilot projects. Then they hit a wall. The demos work beautifully. The business case looks compelling. But somehow, the value never materializes at scale.
This gap between adoption and execution defines the current AI moment.
Devoteam UK recognized this pattern and built something different. Their partnership with ServiceNow created ADAPT, the AI and Data Acceleration Program for Transformation. The program converts AI vision into measurable business outcomes within four weeks.
Four weeks sounds aggressive. That's the point.
The traditional approach to AI implementation mirrors how companies approached digital transformation. Long planning cycles. Extensive requirements gathering. Phased rollouts over quarters or years. But AI transformation requires different thinking. The technology evolves too quickly. Competitive advantages compound too fast. Waiting for perfect conditions means permanent disadvantage.
Devoteam's bet reflects this reality. CEO Stanislas de Bentzmann projects AI-related services will grow from 5% of their business today to 50% by 2028. They're targeting €2 billion in turnover, with half coming from AI projects. These aren't aspirational numbers. They're strategic commitments backed by a fundamental shift in how they deliver value.
The winners in AI implementation follow a counterintuitive pattern.
Companies using generative AI achieve an average ROI of $3.70 for every dollar spent. Top performers hit $10.30 per dollar invested. The gap between average and exceptional isn't about better algorithms or more data. It's about implementation discipline.
AI leaders follow what researchers call the 10-20-70 rule. They put 10% of resources into algorithms, 20% into technology and data, and 70% into people and processes.
Read that again. Seventy percent goes to people and processes.
The biggest obstacle to AI success isn't technical. Most implementation challenges stem from organizational factors: unclear ownership, misaligned incentives, inadequate training, resistance to workflow changes. Companies that treat AI as purely a technology problem join the 74% that can't scale value.
ADAPT addresses this reality head-on. The four-week timeframe forces clarity. Organizations can't spend months debating theoretical use cases. They must identify specific business problems, define measurable outcomes, and commit to implementation. The compressed timeline eliminates the drift that kills most AI initiatives.
The program structure reflects implementation realities. Week one focuses on discovery and alignment. Week two develops the strategic roadmap. Week three builds the technical foundation. Week four delivers initial deployment and measures early results.
This velocity matters more than perfection.
Every month spent planning gives competitors time to learn. Their AI models ingest new data and improve accuracy. Their teams develop institutional knowledge about what works and what doesn't. Their processes adapt to AI-augmented workflows. Meanwhile, companies waiting for ideal conditions fall further behind.
The ServiceNow platform provides the infrastructure that makes rapid implementation possible. Their AI capabilities integrate across enterprise functions, from IT service management to customer service to HR operations. This integration eliminates the fragmentation that typically slows AI adoption.
Global leaders including Adobe, Aptiv, Visa, and Wells Fargo use ServiceNow AI to drive measurable outcomes. They're not running experiments. They're generating business value at scale.
The strategic imperative is clear. AI adoption without execution capability creates costs without benefits. Organizations pay for tools they can't use effectively. They hire talent that can't deliver results within existing structures. They launch initiatives that never progress beyond proof of concept.
The alternative requires different thinking. Start with specific business outcomes, not technology capabilities. Identify clear ownership and accountability. Invest heavily in organizational change alongside technical implementation. Move fast enough to learn before the competitive landscape shifts.
Devoteam's growth targets reflect confidence in this approach. Doubling revenue with half coming from AI projects means they're betting their business on execution capability. They're not selling AI tools or running pilots. They're delivering transformation that shows up in client financial results.
The window for building AI capability is closing faster than most executives realize. Organizations that develop implementation discipline today will have significantly more refined systems than those starting later. The learning compounds. The competitive gaps widen.
The question isn't whether to adopt AI. Adoption is table stakes. The question is whether you can execute well enough to generate value before your competitors establish unassailable advantages.
Seventy-four percent can't answer yes to that question yet. The 26% who can are pulling away fast.
