People + AI: An executive’s guide to uniting talent and technology

Key takeaways for executives

Organizations succeed with AI when they align technology with workforce readiness, redesign roles around human-AI collaboration, and lead with clear governance and change management. Executives must move beyond automation to augmentation, investing in skills, mindsets, and operating model transformation to unlock measurable ROI.

Technology alone doesn’t transform organizations. People do.

From manufacturing to health, finance to government, the adoption of artificial intelligence (AI) represents a profound paradigm shift: redefining organizational strategy, structure and culture. Leaders who recognize and embrace this transition are better positioned for sustained success by moving from:

• Tools to thinking partners: AI now reasons, generates and adapts—acting less like a tool and more like a collaborator in decision-making, creativity and strategy.
• Efficiency to capability expansion: AI enables entirely new types of work and value creation, expanding possibilities rather than just enhancing efficiency.
• Individual productivity to system transformation: AI reshapes operating models, workflows and business models, requiring redesign rather than incremental role changes.
• Skills to mindsets: AI adoption requires shifts in mindset and culture, going beyond technical skills training to rethinking roles, trust, ethics and governance.
• Linear to exponential change: Rapid advances (e.g., large language models, generative AI) outpace traditional change cycles, compelling faster, more dynamic adaptation.

Results from CGI Voice of Our Clients* show that 82% of organizations have adopted AI strategies and 69% of executives indicate difficulty hiring IT talent.This gap between ambition and workforce readiness highlights a critical need: aligning AI investment with strategic, human-centered transformation.

What are executives expecting from AI transformation?

Executives expect AI to deliver measurable business outcomes—not just efficiency gains. This includes increasing capacity, improving decision-making, accelerating processes and generating clear return on investment. AI has the potential to reshape the capability base of an organization. They’re asking:

• Can we double capacity without adding new people?
• Can we drive both growth and productivity?
• How can AI enhance service delivery, streamline regulatory processes or improve outcomes?
• How can we introduce AI without alienating our people?

Unlocking the value of AI

The value of AI can only be unlocked when organizations pair investments with a strategic, human-centered transformation that promotes a culture of ownership and respect with the introduction of AI. Leaders must set the expectation that AI tools will be used to their full potential. By equipping teams with fit-for-purpose AI tools, embedding clear guardrails and fostering a culture of experimentation and structured feedback, organizations can empower employees to enhance outcomes and co-create the future.

To succeed, organizations must embrace the shift from automation to augmentation—rethinking how AI and humans collaborate to deliver impact. They must train their teams and redesign operating models around AI’s capabilities. This means executives not only endorse AI adoption but model the behavior by actively leveraging it in their own decision-making, signaling its strategic importance. This transformation requires more than new tools; it calls for clear governance and a bold executive vision.

Organizations that lead with a commitment to people-first innovation, measurable outcomes and long-term adaptability will unlock greater ROI and define the future of their industries.

What is workforce readiness?

Workforce readiness is an organization’s ability to equip employees with the skills, tools, and mindset needed to effectively work with AI systems. It is one of the six core elements of a scalable AI ecosystem alongside data, strategic alignment, infrastructure, governance and security. Without an engaged, capable team, even the best AI technologies struggle to deliver business value.

This viewpoint is part of our broader perspective on building enterprise- ready AI. To explore how these elements connect, read our paper on Navigating an AI ecosystem: Scaling for impact, which outlines how organizations can scale AI outcomes through an integrated, strategic approach.

Why do organizations need to rethink work in the age of AI?

AI is changing what work is, how it gets done and who does it. From frontline service roles to strategic planning, AI is optimizing entire functions and accelerating decision-making. Moreover, it’s raising expectations for adaptability.

And yet, despite the pace of technological advancement, many organizations are still operating with legacy mindsets and workflows. The result? A growing disconnect between AI’s capabilities and an organization’s ability to benefit from them.

In many cases, it’s not the technology that’s underperforming; it’s the organization’s capacity to learn and absorb it. A Fortune article cites an MIT study that reveals a “learning gap — people and organizations simply did not understand how to use the AI tools properly or how to design workflows that could capture the benefits of AI while minimizing downside risks.”

To that end, while AI pilots flourish in labs and leadership decks, implementation often stalls when change management is under-resourced, adoption lags and technology capabilities are outdated. Compounding the challenge, many organizations select sub-optimal use cases for initial AI deployment or lack a cohesive rollout and change adoption strategy. Even the best technology and implementation plans will falter without engaged, prepared teams at the core of AI transformation.

Consider how this is playing out across key industries:

Health

AI is streamlining diagnostic imaging, clinical note-taking and even surgical planning. Yet, frontline clinicians often report they haven’t been trained to trust or effectively use these tools. Without investing in developing the skills and confidence to work effectively with AI, health systems risk operational friction, clinician burnout and potentially poor patient outcomes.

Financial services

GenAI can reportedly automate up to 90% of IPO prospectus drafting in a matter of hours—an 8-week task previously owned by teams of analysts. But now firms face a different challenge: redeploying highly skilled professionals for advisory and oversight roles instead of transactional output.

Government

Agencies are piloting AI for grant evaluation and fraud detection. But regulatory constraints, limited change capacity and hiring models make it difficult to pivot with speed.

Manufacturing and utilities

AI is being deployed for predictive maintenance, automated inspections and energy load optimization. Yet, these systems are only as effective as the workers who use and retrain them.

What separates successful AI adopters from those that struggle?

Early movers design for disruption—changing consumer demands, regulatory shifts and market dynamics—instead of waiting for it. Forward-thinking organizations are embedding AI into job design, not just tools. They’re retraining at scale. They’re rethinking KPIs. And they’re doing all of this with a people-first lens.

This is why the real challenge of AI isn’t technical—it’s managing change. Organizations that view AI as a strategic catalyst, not just an IT initiative, will shape the future of work itself. That future isn’t waiting somewhere down the road—it’s being built right now, in every decision companies make about how they lead, reskill and empower their people.

What’s the Difference Between AI Automation and Augmentation?

Automation and augmentation are often conflated, but for leaders, the distinction is everything.Automation seeks efficiency through elimination—replacing tasks(and sometimes roles) with machines. AI augmentation is the use of AI to enhance human capabilities rather than replace human roles—unlocking new potential, not just reducing cost.

Organizations that aim only for automation risk narrowing the role of humans to oversight or exception handling. Those that embrace augmentation design AI as a collaborative force, empowering teams to think faster, make better decisions and deliver more personalized, strategic outputs.

Yet, few organizations have reached that point. According to CGI Voice of Our Clients results, only 5% have integrated AI into several or all business processes. This signals a significant opportunity for organizations to tap into augmentation to drive value.

For instance, in the utilities industry, predictive AI doesn’t replace maintenance crews, it allows them to focus on proactive service instead of reactive repairs. In state government, AI-powered systems streamline benefits processing, such as unemployment claims or Medicaid eligibility determinations. For example, several state health and human services agencies now use AI to pre-screen applications and flag incomplete or high-risk cases. But caseworkers still conduct final reviews, handle complex scenarios and provide the personalized support constituents need. In each case, AI amplifies human strengths, it doesn’t replace them.

The leadership implication? Executives must redesign roles and KPIs around human-AI collaboration. What was once a rote reporting function becomes insight generation. Operational roles can expand into more strategic work, but only if organizations invest in developing the skills and mindsets needed to unlock that potential.

The question is not “what can AI automate?” but “how can AI amplify our people’s capabilities?”

Building a future-ready workforce

Too often, organizations develop bold AI strategies without a clear view of whether their teams are equipped to execute them. Bridging this gap requires tighter alignment between planning and enterprise strategy, ensuring that workforce decisions evolve in lockstep with technological ambitions.

Organizations should establish cross-functional teams that embed change management from the start. This structured approach helps guide people through the transition, address resistance and ensure AI adoption becomes part of everyday workflows. The result: AI solutions that are technically sound, operationally viable and aligned with real-world capability on the ground.

Effective change management builds communication, training and feedback loops into every stage of AI adoption—helping employees understand the ‘why,’ develop skills, and take ownership for transformation.

Tomorrow’s talent strategy must encompass new skills, tools and mindsets built around adaptability, continuous learning and human-AI collaboration.

What Is agentic AI and how will it change the workforce?

At the center of this shift is agentic AI. Agentic AI refers to autonomous systems that operate more like digital coworkers than tools. These agents manage multistep tasks with limited input, adapt in real time and simulate decision-making. Already in use across industries— from sales operations to strategic planning—they’re accelerating demand for new competencies, governance models and role definitions.

Their potential is vast, but they introduce a new layer of complexity. Leaders must determine which tasks should remain human-led, which can be delegated to agents, and how to evaluate performance and accountability in this new dynamic.This isn’t just a technical transition—it’s a people and capability transition. Successfully integrating agentic AI depends on cultivating a team equipped to guide, validate and collaborate with these systems.

Leading organizations are meeting the challenge with structured, scalable training and by fostering AI fluency across functions. Business analysts are learning to craft better prompts. Product managers are validating outputs. HR leaders are shaping responsible AI frameworks.

From an industry perspective:

• Financial services professionals are shifting from performing analysis to interpreting AI-generated insights.
• Healthcare clinicians are learning to apply judgment alongside AI recommendations.
• Government civil servants are being trained to oversee AI-enhanced services like automated benefits processing, ensuring that efficiency doesn’t come at the expense of transparency or fairness.

Best practices for accelerating change include:

• Job clustering and tailored strategies: Group roles based on how much and how quickly AI will affect them, then apply change management and learning approaches for each cluster.
• AI academies and bootcamps: Create internal hubs for hands-on learning tied to real business use cases.
• Champion networks: Empower early adopters to demo tools, share wins and drive cultural change.
• Phased rollouts and pilots: Use targeted deployments to validate performance, refine change approaches and gather feedback before scaling.

Don’t wait for a perfect curriculum. Start with what’s needed now, scale what works and evolve as fast as your industry demands.

Our own AI transformation

At CGI, we don’t just advise clients on AI transformation— we live it ourselves. By proactively implementing AI across our own operations, we apply firsthand lessons to help clients achieve AI-driven success with confidence and speed. Our internal journey has allowed us to identify real-world challenges, pilot solutions in controlled environments and refine our strategies before deploying them at scale. Through this experience, we’ve seen the power of AI in action.

• Operational excellence: From automating administrative tasks to improving decision-making, we’ve leveraged AI to accelerate our workflows, improve data access and streamline service delivery. As we adopt and scale AI tools across our software development life cycle activities, we are seeing productivity gains of up to 40%, enabling teams to deliver faster, optimize quality and focus more time on higher-value outcomes.
• Mission ready AI: To meet the highest standards of security and compliance, CGI’s U.S. federal operations developed an internal AI solution for over 7,800 employees. Designed to operate securely within a U.S. federal environment, this platform supports document generation, code development, research and data analysis while preserving strict information handling protocols. The result? A secure AI deployment that delivers measurable results, without compromising regulatory or operational standards.
• Empowering our people: AI amplifies our teams’ expertise, uncovering patterns and possibilities so they can design solutions that directly fit each client’s unique challenges.
• Right fit solutions: We use our AI tools to analyze client objectives, industry context and technical requirements, then assemble the most relevant offerings and services from our global portfolio. This allows us to design tailored solutions that align to each client’s needs, accelerating value delivery while ensuring every recommendation is grounded in proven capabilities and real-world outcomes.
• Accelerating adoption: We developed a custom AI adoption approach to accelerate the integration of AI into our ways of working. Through pilot phases, we achieved significant outcomes and refined our methodology—for example, turning 73% of initial slow adopters into active weekly users. We are now bringing this proven approach to our clients through the AI Adoption Acceleration Framework (A3F).

By walking the path ourselves, we help clients avoid common pitfalls and fast-track their transformation with real insight, proven strategies and trusted AI governance models.

What is the role of executives in AI transformation?

AI transformation is as much about trust as it is about technology. Without it, adoption stalls. With it, momentum builds. But trust isn’t a communications issue—it’s a leadership strategy.

To lead with trust, organizations must embed change leadership. This means communicating limits and capabilities, building ethical guardrails and offering channels for real-time feedback. AI talent strategy cannot be delegated to IT or HR—it’s a C-suite issue that touches every line of business. Executives must work as a team and move from passive supporters to active champions of AI integration.

• CEOs set the vision: How does AI align with the company’s mission, culture and growth strategy
• CIOs/CTOs ensure flexible, ethical and scalable AI infrastructure that supports experimentation without compromising governance.
• CFOs define ROI, shifting from cost savings to value generation.
• CMOs align AI offerings to meet market demands and effectively communicate the transformation to customers and employees.
• CHROs manage talent development and organizational design and ensure equitable access to training and advancement opportunities during AI-driven change.

Successful AI leaders:

• Pilot visibly, using AI themselves and sharing wins
• Fund learning, not just tools
• Reward curiosity, not just productivity
• Measure adoption, proficiency and utilization
• Measure outcomes

In the age of AI, leadership is not about having all the answers—it’s about asking the right questions, modeling the behavior and resourcing the journey.

Guiding AI workforce transformation

The path forward is not automation or augmentation. It’s not technical or human. It’s both. AI will rewrite how value is created. But who will shape the future, and who will be shaped by it?

Organizations that blend AI adoption with strategic, people-first transformation will gain more than ROI—they’ll gain resilience, relevance and a reputation for responsible innovation.

For business leaders, this is your moment:

• Rethink roles and workflows.
• Reskill and elevate your workforce.
• Redesign governance models for AI-era agility.
• Reaffirm your core values that will guide your journey.

The future won’t wait. Organizations that design for disruption, not just react to it, will define the next decade of competitive advantage and human achievement.

The age of AI isn’t about replacing people. It’s about reimagining what people and organizations are capable of achieving.

The right partner by your side

As organizations move from pilots to enterprise-wide implementation, workforce readiness becomes a critical enabler of success. Choose a partner with deep industry expertise and proven change leadership frameworks to help you align your talent, processes and technology for long-term success.

Whether you’re preparing teams to work alongside AI, scaling adoption across business functions or redesigning roles around augmented capabilities, we bring practical experience and human-centered strategies to guide your transformation.

The right partner doesn’t just deploy tools—they help you build the skills, structures and culture needed to thrive in an AI-powered future.

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