CGI highlights importance of hiring and retention alongside technology
Organisations are deploying artificial intelligence into core operations faster than they can recruit and reskill the workers needed to run it – reframing the AI conversation as a hiring and retention problem before it is a technology problem, according to CGI.
Currently, nearly 70% of organisations report difficulty recruiting IT talent, while 52% say talent shortages materially affect their programs and execution capacity, based on the report.
Cost pressure remains the number one constraint facing organisations, according to the research, and 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,” says 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.”
Recently, Amazon founder Jeff Bezos said that AI adoption will lead to a "labour shortage," as he rejected assumptions that the technology will cost humans jobs.
AI adoption outpacing enterprise readiness
Generative AI implementation has climbed by 30 percentage points over the past two years, CGI reports, and 62% of organisations are now applying AI to core business and operational processes. Adoption, in other words, is no longer the bottleneck.
Readiness is. Only 40% of organisations have an enterprise AI strategy, just 20% extend that strategy across their broader ecosystem, and only 51% quantify the results of their AI adoption.
CGI frames the challenge as one of execution rather than ambition. "With AI adoption accelerating, the priority is now execution and value realization," says Dave Henderson, Chief Technology Officer, CGI.
More than one in five Canadian workers (22%) used generative artificial intelligence (GenAI) at work in the year ending in mid-2025, and use is rising quickly, Statistics Canada (StatCan) recently reported.
Managed services reshaping decisions
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.
CGI also notes that clients are increasingly consolidating toward fewer, trusted partners able to combine business consulting, systems integration and digital reengineering to deliver end-to-end outcomes. The firm warns that applying AI to fragmented data, legacy systems and outdated operating models often increases complexity rather than delivering measurable value.
Henderson says the opportunity lies in integration rather than isolated pilots. The focus for organizations, he says, must be to “move beyond isolated AI use cases toward embedding AI into complex enterprise environments to deliver tangible results and sustainable competitive advantage.”
Pressure to become adaptive
The research situates the talent and readiness gaps within a wider push for organisational 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 prioritising 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.
Most large organisations 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.
