Bridge the GenAI gap: Transform pilots into profits through carefully planned intelligence

Bridging the GenAI divide:Converting pilot to profit withorchestrated intelligence TP.ai FAB The “Great Disconnect” in enterprise AI 95% The race to adopt generative artificial intelligence (GenAI) has createda significant gap in the business world. On the one hand, companiesare investing billions, launching pilot programs with enthusiasm. On theother hand, a staggering reality is emerging — most of these initiatives of GenAI pilots fail,according to MIT Recent studies paint a clear and somewhat concerning picture. A 2025 MIT report foundthat an astonishing 95% of enterprise GenAI pilots fail to move from testing to productionwith measurable impact. Similarly, Gartner research notes that most organizations remainstuck in the pilot phase, focusing more on internal productivity tweaks than on true This isn’t just a technology problem; it’s a strategic one. We call it the GenAI divide — thechasm between superficial adoption and genuine, profitable transformation. Companiesare discovering that off-the-shelf AI tools, while impressive in demos, often fall short whenintegrated into the complex, real-world workflows of a large enterprise. They lack the So, how do you join the successful 5%?The answer lies in a new way of thinking. It requires moving beyond simply implementing tools and toward a model of orchestrated intelligence. This approach recognizes that realimpact comes from harmonizing advanced technology with your most valuable asset —your people and their deep industry expertise. It’s about creating a single, adaptive system Read on to understand the common pitfalls of AI adoption, learn about actionablestrategies, and examine real-world case studies. Understanding the GenAI divide The promise of GenAI is undeniable. Leaders across every industryare eager to harness its power to boost efficiency, create new revenuestreams, and revolutionize customer experiences. Yet, the road fromambition to achievement is proving to be more challenging than initiatives, but they often result in what the report calls “high-adoption, low-transformation” mode. What does this mean? Employees might be using generic AI chatbotsfor simple, low-value tasks, but the core business processes remainuntouched. The transformative power of AI to reshape workflows, The 95% problem: Why most AI pilots failThe statistics are stark. According to a landmark 2025 MIT study, approximately 95% of custom GenAI pilots fail to scale and delivermeasurable business impact. This widespread failure isn’t due to alack of effort or investment. Billions of dollars are being poured into AI KEY REASONS FOR THIS FAILURE INCLUDE: Focusing on the wrong metricsMany companies measure success byadoption rates (e.g., logins)rather than business outcomes The “one-size-fits-all” illusionGeneric, off-the-shelf AI toolslack the specific context andmemory needed to handle Implementing in a silo Many companies attempt to build proprietaryAI systems internally, but MIT’s research showsthat partnering with specialized vendors is Bridging the GenAI divide: Converting pilot to profit with orchestrated intelligence The illusion of progress: Adoption vs. adaptationGartner’s 2024 “Does GenAI Improve CX?” survey reinforces this reality. It was found that most companies are still in the testing or pilot phase, focusingprimarily on improving internal productivity, not driving customer-facinginnovation. While efficiency gains are valuable, they represent only a fraction of This creates an illusion of progress. A company might celebrate that 80%of its workforce has used a new AI tool. However, if that usage is limited tosummarizing emails or drafting routine communications, the organization True progress occurs when AI is deeply embedded into high-value workflows,fundamentally changing how work gets done. This is the difference betweenan employee asking a chatbot a question and an AI-orchestrated system that The unseen engine of success: Embracing operational friction Conventional wisdom suggests that the ideal technology is“frictionless”. We strive for smooth, seamless experiences. However,when it comes to enterprise AI transformation, recent findingssuggest that avoiding friction is precisely why so many initiatives fail. The three faces of friction To harness friction, you must first understand its sources. It typically manifests inthree interconnected forms: As a Forbes analysis of the MIT report powerfully states, “Frictionisn’t failure. It’s what keeps your tires on the road.” The 5% of companies that succeed treat friction as a design input.They recognize that resistance reveals where systems must adapt,where workflows need to be redesigned, and where governance has For the 95% of companies that fail, this friction becomes a dead end. The pilot is deemed unsuccessful, and the initiative is abandoned.But for the 5% that succeed, friction is not an obstacle — it’s a critical part of the process. Introducing orchestrated intelligence (OI) U