Organizations are deploying AI into core operations faster than they can recruit and reskill the people needed to run it, turning the AI conversation into a hiring and retention problem before it becomes a technology problem. Nearly 70% of organizations report difficulty recruiting IT talent, and 52% say talent shortages materially affect their programs and execution capacity, according to CGI's 2026 Voice of Our Clients research.
Cost pressure remains the top constraint facing organizations. At the same time, 45% of executives say legacy systems significantly challenge their data and AI strategies. Together, those pressures narrow the room employers have to fund the recruitment, training and redesign of roles that AI programs require. The squeeze is pushing leaders toward rebuilding internal capability rather than chasing frontier technology.
"Executives are navigating an environment defined by rising complexity, from regulatory pressures to fragmented systems, while still being expected to deliver measurable outcomes," said Tim Hurlebaus, CGI President and CEO. "Our 2026 Voice of Our Clients insights show a clear evolution toward digital engineering and reengineering initiatives, as organizations build new capabilities and modernize legacy environments to scale AI and achieve their digital transformation outcomes."
Adoption is no longer the bottleneck
Generative AI implementation has climbed by 30 percentage points over the past two years, and 62% of organizations are now applying AI to core business and operational processes. Adoption, in other words, is no longer the bottleneck. Readiness is. Only 40% of organizations have an enterprise AI strategy, just 20% extend that strategy across their broader ecosystem, and only 51% quantify the results of their AI adoption.
"With AI adoption accelerating, the priority is now execution and value realization," said Dave Henderson, Chief Technology Officer at CGI. More than one in five Canadian workers used generative AI at work in the year ending mid-2025, and use is rising quickly, Statistics Canada recently reported.
Most large organizations are investing in AI training without defining what AI competency looks like in specific roles, leaving managers under-prepared and employees unconvinced their employers are ready for AI-driven change, according to previous research from Acorn. This gap sits at the center of the readiness challenge: organizations have the tools but not the defined workforce planning to support them.
Managed services and partner consolidation
In response to the readiness gap, the CGI research finds C-level executives shifting toward substantial and selective managed services models to strengthen delivery capacity and support scalable, AI-enabled transformation. Clients are increasingly consolidating toward fewer, trusted partners able to combine business consulting, systems integration and digital reengineering to deliver end-to-end outcomes.
Henderson said the opportunity lies in integration rather than isolated pilots. The focus for organizations must be to "move beyond isolated AI use cases toward embedding AI into complex enterprise environments to deliver tangible results and sustainable competitive advantage." CGI warns that applying AI to fragmented data, legacy systems and outdated operating models often increases complexity rather than delivering measurable value.
The resilience imperative
The research situates the talent and readiness gaps within a wider push for organizational resilience. Just 25% of executives rate their operating models as highly agile, even as 70% identify technology and digital acceleration as the most impactful macro trend shaping their strategies. At the same time, 52% of executives are prioritizing data sovereignty and local cloud strategies, while shifts in the world economic order and the reconfiguration of supply chains continue to rise as a source of pressure.
For HR, that environment raises the premium on an adaptive workforce that can absorb the continual reengineering of roles and processes such conditions demand. The ability to define AI competency by role, rather than offering generic training, is becoming a direct input into whether organizations can execute on their AI strategies. For HR leaders building that capability, an AI Learning Path for CHROs addresses workforce analytics, recruitment automation and talent management in the context of AI-driven transformation.
Why this matters for HR leaders
The data reframes AI adoption as a workforce problem with a timeline. When 52% of executives say talent shortages directly reduce their program capacity, and only 40% have an enterprise AI strategy, the gap between technology deployment and people readiness becomes a business risk that HR owns. The organizations closing this gap are not just funding training-they are defining what AI competency means for each role, redesigning workflows around that definition, and building the internal capacity to do both continuously. For HR teams, the signal is clear: AI for Human Resources is shifting from a support function to a core execution capability.
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