Global Business Services (GBS) organizations are facing an unprecedented productivity squeeze, with workloads forecast to grow 15% in 2026 while staffing increases lag at just 10%. This widening gap is forcing enterprise leaders to move beyond AI pilots and fundamentally reimagine how work gets done, according to The Hackett Group's 2026 GBS Key Issues Study, which surveyed leaders across the world's largest organizations. The numbers paint a stark picture: a 5% productivity gap and an 8% efficiency gap represent the most significant imbalance GBS leaders have faced in years. Budget increases of just 7% further constrain resources, leaving organizations with limited options. Rather than hiring their way out of the problem, leading companies are deploying generative AI and automation as strategic transformation engines, not incremental productivity tools. What Results Are Early AI Deployments Actually Delivering? The good news: AI is already working. Nearly 90% of GBS leaders report that AI is reshaping routine tasks, and more than half see measurable effects on complex work. Early Gen AI deployments are delivering concrete improvements across multiple dimensions: - Customer Experience: A 13% improvement in how customers perceive service quality and responsiveness - Employee Engagement: An 11% gain in workforce satisfaction and productivity when AI handles routine work - Service Quality: An 11% increase in the consistency and accuracy of service delivery - Productivity Boost: A 10% overall productivity improvement across GBS operations Interestingly, cost reduction and full-time equivalent (FTE) savings have been more modest, suggesting that AI's primary value lies in elevating service performance rather than simply reducing headcount. This shift in focus reflects a maturation in how enterprises think about AI's role. One-quarter of GBS organizations now expect broad deployment in 2026, up from under 10% a year ago. Customer service leads the charge with 32% planning wide-scale deployment, followed by information technology at 25% and supply chain at 21%. Even in established GBS domains like finance, procurement, and human resources, between 13% and 18% are preparing for broad rollout, with a majority actively piloting or selectively deploying AI. Why Are Organizations Struggling to Turn AI Confidence Into Results? Here's the paradox: while GBS leaders recognize AI's potential, confidence in achieving core objectives is actually declining. Seventy percent of GBS leaders rank cost leadership as a top priority, and 69% prioritize value creation. Yet only 30% now express high confidence in meeting cost reduction targets, down from 44% last year. Just 21% are highly confident in achieving value creation goals, down from 41% last year. "Facing this kind of pressure, the organizations that will come out ahead are those that move beyond adopting AI as a surface-level add-on and instead use it to fundamentally reimagine how work gets done, combining digital innovation with operational resilience," said Martijn Geerling, Europe Applied Intelligence practice leader and GBS Applied Intelligence program leader at The Hackett Group. Martijn Geerling, Europe Applied Intelligence Practice Leader at The Hackett Group The core issue is execution discipline, not strategic intent. Nearly three-quarters (72%) of leaders cite misalignment between expected and actual AI benefits as a significant concern, tied with process complexity and technology immaturity. Rising workloads, constrained budgets, and uncertainty around how to operationalize AI execution are widening the gap between ambition and outcomes. Notably, concerns around data privacy, regulatory issues, and ethics have declined in priority, signaling a shift from whether to adopt AI to how to deploy it effectively. The conversation has moved from "Should we do this?" to "How do we make this work?". How to Close the Productivity Gap: Five Strategic Priorities for 2026 Leading GBS organizations are focusing on five concrete priorities to move beyond experimentation and achieve process-level transformation with clear business cases: - Expand Automation Into Higher-Value Work: Move AI beyond routine tasks into complex activities where human judgment was previously required, multiplying impact - Build Digital Skills and Capabilities: Invest in workforce training to help employees work effectively alongside AI systems and manage new workflows - Align Cost Optimization With Value Creation: Stop treating cost reduction and value creation as separate goals; design AI deployments that achieve both simultaneously - Strengthen Data Integrity and Governance: Ensure data quality and proper governance frameworks so AI systems have reliable inputs and operate within appropriate guardrails - Redefine Performance Management: Measure success beyond traditional cost metrics to include customer experience, employee engagement, service quality, and innovation By combining process intelligence, benchmarking, and targeted AI deployment, organizations can identify where automation and digital labor deliver the greatest productivity and service improvement. How Are Outsourcing Relationships Evolving? As Gen AI adoption expands, outsourcing relationships are also transforming. Business process outsourcing (BPO) providers are embedding AI into service delivery to transform manual labor into digital labor, improving experience, quality, and workforce effectiveness. Organizations increasingly seek partners that can deliver AI-enabled solutions rather than simply lower-cost labor. For GBS leaders, these partnerships provide another option to accelerate the shift from manual labor to digital labor while accessing AI capabilities and investment scale that would be challenging to replicate internally. "AI and automation are becoming foundational to GBS performance. Organizations that focus on process-level opportunities and deploy AI with clear, fact-based business cases are already seeing measurable gains in productivity, service quality, and customer experience, and that performance gap will continue to widen," explained Amar Changulani, research director at The Hackett Group. Amar Changulani, Research Director at The Hackett Group The bottom line: the productivity crisis facing Global Business Services is real, but it's also creating an opportunity for organizations willing to move beyond surface-level AI adoption. Those that treat AI as a strategic transformation engine, backed by clear business cases and disciplined execution, are already pulling ahead. The performance gap between leaders and laggards will only widen as 2026 progresses.
