Every service provider we interviewed has AI pilots underway. Many report impressive results: 50% efficiency gains here, 90% accuracy improvements there. Yet few have scaled these successes into enterprise-wide transformation. This "pilot paradox" emerges as a defining challenge.
The pilot paradox stems from several causes:
Success metrics misalignment. Pilots optimise for impressive metrics that don't translate to business value at scale. A chatbot handling 90% of queries brilliantly might fail if it can't integrate with systems or hand off complex issues smoothly.
Resource constraints. Pilots receive dedicated resources and hand-picked teams. Scaling requires same results with standard resources and typical employees.
Technical debt accumulation. Each pilot creates its own infrastructure and governance. Scaling requires rationalising these into coherent architecture.
Organisational readiness gaps. Pilots succeed in pockets of enthusiasm but scaling requires organisation-wide change.
The pilot paradox stems from several causes:
Success metrics misalignment. Pilots optimise for impressive metrics that don't translate to business value at scale. A chatbot handling 90% of queries brilliantly might fail if it can't integrate with systems or hand off complex issues smoothly.
Resource constraints. Pilots receive dedicated resources and hand-picked teams. Scaling requires same results with standard resources and typical employees.
Technical debt accumulation. Each pilot creates its own infrastructure and governance. Scaling requires rationalising these into coherent architecture.
Organisational readiness gaps. Pilots succeed in pockets of enthusiasm but scaling requires organisation-wide change.
Successful organisations navigate through "land and expand" approaches with crucial differences from traditional strategies.
Modhura Roy from Cognizant articulates: "We always start small and then expand so we prefer to say land and expand. We will start with something small which we'll try and deliver impact in maybe 90 days and based on that, we take it forward to expand into other areas." She emphasises this isn't random: "We try to understand what is the vision, what are the different milestones we need to go through to reach that particular vision."
This approach, where each pilot builds toward transformation vision, distinguishes successful organisations from those stuck in pilot purgatory.
Vijay Raaghavan from Fractal provides insight: "This requires a balanced approach as there's no definitive right or wrong answer. In my experience, quick wins often lead to more scalable solutions -- you typically can't jump directly to large-scale implementations. We start with small proof of concepts to validate the art of the possible. These quick wins build credibility and confidence with both clients and internal sponsors."
He continues: "Once we've demonstrated success with these smaller initiatives, we can expand to broader, more sustainable projects -- what I call a 'land and expand' approach. Even when a quick win doesn't scale immediately, it provides valuable insights into possibilities and limitations that inform future implementations."
Successful navigation requires several elements:
Selective pilot selection.
Rather than pursuing every AI use case, choose pilots building toward transformation vision. Each should advance broader capabilities.
Foundation building.
Use early pilots to build data infrastructure, governance frameworks, and change management approaches enabling future scaling.
Value articulation.
Moving from pilot to scale requires clear value articulation resonating with executives and employees alike.
Quick iteration cycles.
Compress timeline from pilot to production decision. Set clear go/no-go criteria and decision points.
Cross-functional orchestration.
Scaling requires coordination across IT, operations, finance, and business units.
Jon McClay from Baker McKenzie highlights strategic selection: "We take a coordinated approach rather than allowing siloed initiatives. We have individuals focused on data governance, global deployment projects for common AI tools, and strategic initiatives that help identify where we can find the greatest benefits."
Financial considerations add another dimension. Ankur Saxena highlights: "Investment prioritisation, the capital requirements are definitely going to be challenging ones." While pilots often use innovation budgets, scaling requires major investment and clear ROI projections.
Industry leaders find the key lies not in pilots themselves but what happens around them. Vinti Mathur from Genpact emphasises planning: "When we are helping clients, we start looking at the business case and the road map which is there. We detail out what is it that can be delivered or what is the impact that can be created."
This business case development creates foundation for scaling decisions. Technical feasibility isn't enough; organisations must demonstrate business value, operational readiness, and clear scaling path.
Timeline pressure intensifies the paradox. With 12-month windows, there's limited time for extended pilots. This forces disciplined experimentation: fail fast, learn quickly, scale with speed.
The path from pilot to scale isn't linear but iterative and navigable with the right approach. Successful organisations treat pilots as learning experiences informing broader transformation. They build foundations during piloting allowing quick scaling. Most importantly, they maintain focus on advancing transformation rather than creating isolated innovation islands.
The message: pilots are necessary but not sufficient. Organisations successfully navigating AI transformation view pilots as journey steps, not destinations. They plan for scale from day one, build supporting foundations, and focus on business value over technical metrics. In doing so, they escape pilot purgatory and achieve enterprise transformation delivering real competitive advantage.
Success in scaling pilots requires building an intelligent workforce capable of working alongside AI.
About Enate
Enate is the leading SaaS solution for business services. Enate orchestrates work from start to finish, giving clients the visibility and control needed to deliver better services. From email management and data analysis to intelligent document processing, Enate also offers a host of touch-button AI features designed to slash the time spent on manual work. Trusted by global service teams, Enate ensures smooth, consistent operations that help clients perform at their best.