The Human-AI Workforce Journey: 5 Steps for CIOs to Accelerate AI-Readiness
16 January 2026 - ID G00844306 - 27 min read
By Tori Paulman, Shawn Murphy, and 4 more
AI is outpacing your workforce. This research note delivers a practical, five-step roadmap to help CIOs unlock the full value of human-AI collaboration. By leading the way in AI-driven IT transformation, CIOs will establish themselves as the strategic architects of enterprise success in the AI era.
Insights at a Glance
Human readiness for AI lags far behind technology readiness. Many CIOs mistakenly treat “IT workforce readiness” and “general workforce readiness” as separate workstreams, but the IT workforce is the upstream manufacturing plant; if not retooled for AI, it pollutes the downstream environment for the rest of the organization.
- Only 6% of individual contributors have received guidance on the AI skills they need to develop and 41% of AI users struggle to integrate AI into daily routines.1
- Nearly three-quarters of IT workers use personally obtained AI tools or applications for at least some of their work.2
- Only two in 10 CIOs feel their teams are fully ready for AI, and half of CIOs say their need for AI-ready skills is growing faster than talent supply.3
- More than half of CIOs report skills gaps in the underlying technology disciplines necessary for successful AI-augmentation including GenAI, AI, machine learning, and data science.4
The organizations that will succeed are those that recognize AI is not just changing how work happens or who does it, it is fundamentally redefining what “work” means: shifting from shared workflows with routine tasks and well-defined jobs to dynamic, AI-enabled workflows and new forms of value creation. CIOs who lead this evolution by anticipating workforce evolution within IT can set a precedent and establish a framework that other business units can follow, amplifying their impact across the entire workforce.
Five Steps to an AI-Augmented Workforce:
Five Steps to an AI-Augmented Workforce:
- Step 1: Define an AI-Driven Talent Strategy: The cornerstone of a CIO’s leadership agenda must be a clear, uncompromising, AI-augmented IT workforce strategy that directly supports the organization’s AI ambition.
- Step 2: Measure Workforce AI Readiness: Demand rigorous, data-driven measurement of skills to surface deficits that stand between your AI-ambition and IT workforce readiness.
- Step 3: Design the Human-AI Work Dynamic: Design for transformative impact by overhauling workflows, processes, and jobs to maximize the value of human-AI collaboration.
- Step 4: Scale Human Readiness for AI: Avoid lengthy pilots and generic full scale deployments of general purpose AI, instead favoring results-oriented initiatives with business-outcome metrics.
- Step 5: Evolve AI-Augmented Workforce Agility: Hardwire continuous improvement into your operating model. Build a flywheel of rapid iteration, prioritization, and adaptive learning.
Strategic Planning Assumptions
By 2030, 75% of IT work will be done by humans with AI, and 25% of work will be done by AI alone.
By 2027, 75% of hiring processes will include certification and testing requirements for workplace AI proficiency during recruiting.
Issue Context
The Current State: Velocity Without Value
Most organizations are running their AI strategies like drag races. The need for speed leads too many CIOs rushing to launch as many AI pilots as possible without a clear map for how AI will reshape the IT and broader workforce. This focus on sheer speed (number of projects) instead of direction and value (how AI actually helps employees) not only widens the gap in readiness, but also risks turning today’s AI tools into tomorrow’s technical headaches.
- Broad AI deployments without a job and process redesign are widening the human readiness gap. Nearly half of CIOs anticipate that AI-augmentation will lead to skills atrophy, making it essential to have a strategy identifying and preventing skills atrophy.5
- CIOs have a remit to share their AI-augmented workforce insights and influence beyond IT but don’t consistently. Only two in 10 C-suite leaders6 feel highly tech-savvy and executives broadly agree7,8 that the CIO should play a leading role in driving agile, new ways of working across the entire organization.
- CIOs see shadow AI as the top behavioral byproduct resulting from AI-augmentation, while culture change and skills atrophy are expected to be the top impacts over the next three years.
- A lack of visibility into skills hinders meaningful learning journeys by making it difficult to identify both current capabilities and areas for growth. Only 6% of individual contributors say they get advice on what AI skills they’ll need, and 41% of AI users struggle to integrate AI into their daily routine.9
- Change fatigue and resistance thrives because employees are left out of the conversation about how their work will change.
- Employees see AI as a threat that undermines the value of their expertise and experience as rigid, tenure-based job descriptions and activity-based metrics fail to recognize and reward new AI-augmented behaviors.
By 2030, Gartner expects that 75% of IT work will be done by humans working alongside AI, while 25% will be executed by AI alone.
The Future State: Precision and Synchronization
What organizations really need is a Formula 1 racing team: Success is not about speed alone, but about precision, strategy, teamwork, agility and constant adjustments. CIOs must unify the C-suite in architecting new talent strategies, co-leadership, and shared accountability. Building an AI-ready workforce takes a unified vision and shared responsibility.
Key elements of the future state include:
- Strategic workforce planning aligned to business priorities and AI ambition, shaped by the organization’s AI mindset (AI-cautious, AI-opportunist, AI-first).
- Cross functional fusion teams reengineer workflows for optimal human-AI collaboration, with CIOs co-leading an AI agent layer council.
- Dynamic, AI-enabled skills and capability building as the norm, with flexible job descriptions, incentives, and career paths.
- Change woven into every aspect of the AI-driven workforce journey, with skills-based talent deployment and fusion teams increasing commitment and adoption.
- Shared governance and integrated agility, with a cross-functional AI agent layer council (CIO, CHRO, CFO, COO, CMO, CISO, and general counsel) to manage healthy scaling and governance of agentic AI and the AI-augmented workforce.
Impact Brief
The urgency for an intentional AI-driven workforce strategy stems from the breakneck pace of AI innovation; CIOs who fail to modernize their tech talent strategies risk leaving their organizations permanently behind competitors who have successfully unlocked human-AI collaboration.
Without a unified, forward-looking approach, CIOs face the high risk of organizational inertia within their IT teams, where mismatched skills and outdated operating models lead to inefficient processes, wasted technology spend, and missed ROI. By fundamentally redesigning IT jobs in relation to business priorities and AI ambitions, CIOs can move beyond incremental improvements to drive substantial cost savings and competitive innovation for the technology organization.
While CIOs are directly accountable for the IT workforce, they also shape the technology landscape that empowers the entire organization to deliver business outcomes. By partnering with CHROs to align IT talent with business priorities, CIOs can identify best practices that not only strengthen IT, but can be scaled across the broader workforce, transforming IT into a catalyst for enterprisewide AI adoption and impact.
CIOs will start somewhere on this journey and may not follow a linear pathway. To maximize success, CIOs should focus their effort and avoid overload by answering a prioritized set of questions for each step, based on their AI maturity and ambition. Use the links below to jump to the most appropriate step.
More Detail
The Five-Step Journey for a Human-AI Workforce
CIOs should consider this research a compendium to revisit regularly as their AI-driven IT workforce strategy evolves. In addition, not every organization needs to tackle all five steps with equal intensity at once.
Start by aligning your journey steps to your AI ambition:
- If you are AI-cautious, prioritize Steps 1 (vision), 2 (measurement), and 4 (readiness).
- If you are AI-opportunistic, focus on Steps 2 (measurement), 3 (redesign), and 5 (agility).
- If you are AI-first, you may already have covered Steps 1 and 2, double down on Steps 3 (redesign) and 5 (agility).
Step 1: Define an AI-Driven Talent Strategy
Creating a talent strategy for an AI-powered IT workforce isn’t a one-time task. CIOs must keep up with rapid changes in AI, while facing shortages in key technical and nontechnical skills. The line between what people do and what machines do is changing faster than current workforce models can handle. (Read more: Case Study: Redesign Work Processes to Unlock GenAI Transformation.)
Quick win: Keep it simple when drafting your vision for the AI-augmented workforce. Host one brainstorming meeting, one selection/refinement meeting, and put a meeting on the calendar to revisit it quarterly.
CIOs who define their AI-driven talent strategy will answer three questions:
1. How do we establish a vision for a human-AI labor force and ensure it aligns with our organizational goals and priorities?
CIOs must define and clarify their organization’s AI ambition before embracing AI to transform IT (see Figure 2). By aligning IT talent strategy with the organization’s intent for AI-augmentation, CIOs can establish a clear, AI-augmented vision that sets the direction for talent strategy.
The way IT adapts to AI sets technical precedents while also subtly shapes organizational culture and employee expectations. CIOs who intentionally design IT’s AI transformation as a “living laboratory” for enterprisewide learning make it a strategic lever for organizational change management and talent evolution at scale. (Read more: IT 2030: Three Approaches for CIOs to Reinvent IT With AI.)
An AI-first approach is not appropriate for most organizations. It represents a complete overhaul of IT, embedding AI at the core of operations, delivery, and governance.
2. How will AI change our employee experience and shape our culture?
AI ambition is more than a technology strategy; it will be a catalyst for redefining your employment value proposition (EVP). Your approach to AI-augmentation will fundamentally alter the employee experience, from daily workflows to opportunities for growth and recognition. (Read more: CIOs Must Reinvent Their IT Employment Value Proposition to Compete for Top Talent.)
When employees have clarity about what’s changing, they are significantly more likely to adopt the change while maintaining their performance and engagement. This requires a vision for change that describes how work will be different and how business value is created once the change is implemented, helping employees understand exactly what will be expected of them. (Read more: Tool: Measure the Effectiveness of Your Vision for Change.)
AI will upend workforce dynamics as it begins to occupy a space that’s more than just a tool but less than a teammate. Studies have shown that when humans work with effective AI “toolmates” they experience more excitement, energy, and enthusiasm, compared to working with other humans. (Read more: The Rise of the AI Toolmate: Defining AI’s Role in the Workforce.)
How AI Will Influence Your Employee Experience
AI mindset | How AI will influence your employment experience |
AI-cautious IT | Provides stability and consistency in daily work, but may limit exposure to innovation and new skills, potentially leading to routine tasks and slower career growth. |
AI-opportunistic IT | Offers opportunities to engage with emerging technologies and new types of work, creating excitement and career development, but may increase pressure and risk of burnout if not well managed. |
AI-first IT | Immerses employees in fast-paced, cutting-edge roles with high autonomy and learning potential, but can create uncertainty and frustration if support for advancement or recognition is lacking. |
Source: Gartner (January 2026)
3. How can we help humans get the most from collaborating with AI?
The AI strategy must not be developed solely by IT, but be wary of blurred lines in ownership. AI is driving a convergence of IT and HR, the organizations that shape the future of work will be those with a vanguard approach to leadership that unites technology and talent strategy with clear roles and shared accountability. (Read more: Tool: Communication Guide for CHRO & CIO Partnerships.)
CIOs have a rare opportunity to define their role as co-architects of the human + AI labor force. CIOs and CHROs are increasingly participating in fusion teams, becoming co-architects of an agile, AI-augmented workforce strategy. (Read more: Own the AI Agent Layer: The CIO’s Role in Scaling Agentic AI.)
Gartner predicts that by 2029, 20% of organizations will have merged HR and IT functions.
Step 2: Measure Workforce AI-Readiness
Without a quantitative baseline of IT skills, “future-ready” is statistically indistinguishable from unprepared. Fewer than two in 10 CIOs and senior IT leaders10 feel their teams are fully ready for AI, but few know exactly where the skills gaps are. Most organizations today lack real visibility into the bench strength of skills, and promising AI projects without confirming workforce readiness risks failure. (Read more: How CIOs Can Close the IT Workforce Skills Gap for an AI-First Organization.)
— GartnerQuick win: Focus on your “why.” To demonstrate commitment to growth, pinpoint the value of skills and link continuous upskilling/reskilling to diverse career pathways and advancement opportunities. To close gaps — make a list of critical skills and explore AI-enabled IT systems for intelligence that can be used to discover them across your workforce.
CIOs who measure workforce AI-readiness will answer three questions:
1. Do we know what AI skills we need, and how to assess them across our workforce?
Most CIOs are ready to adopt skills-based talent management, but feel their HR partners are not capable of supporting them. CIOs shouldn’t wait for HR to be ready; instead, they should use IT tools to uncover demonstrated skills data and foster versatility and adaptability through personalized learning paths. (Read more: CIOs Adopt Skills-Based Talent Strategies as IT Skills Gaps Linger.)
Promising AI projects without confirming the IT team’s readiness risks falling short and damaging the CIO’s credibility with peers. CIOs must ensure their teams master four essential generative AI skills: use case identification, AI technology fluency, effective prompting, and discernment. (Read more: 4 Generative AI Skills to Master Today.)
Increasingly, CIOs identify human-skills, not tech-skills, as important for an AI-powered future (see Figure 3). CIOs face skills gaps in the technical disciplines necessary for AI success, but increasingly see nontech skills such as innovation, problem solving, and critical thinking skills as important.11 (Read more: How Can CIOs Adopt Gartner’s Digital Core Competencies Model for Workforce Effectiveness.)
2. How can we maintain visibility of skills and update talent profiles as AI changes our work?
A lack of real-time observability of skills is a liability for CIOs. Just over half (51%) of CIOs indicate skills needs are growing faster than their talent supply.12 Real-time skills tracking helps CIOs stay ahead of changing needs, target learning investments, and prevent skills atrophy as AI transforms work. (Read more: CIOs Adopt Skills-Based Talent Strategies as IT Skills Gaps Linger.)
Not all skills require the same frequency of assessment. Technical skills require frequent assessment as they become outdated quickly, while core human skills like critical thinking and problem solving remain valuable over time. Use technology to combine self-assessments, manager feedback, and activity tracking to spot skills gaps and plan development effectively. (Read more: Toolkit: Skills and Competencies Assessment for IT Workforce Effectiveness.)
3. How do we make our skills assessment process transparent, so our teams trust the process?
Skills audits must be positioned as roadmaps for growth, not as hidden assessments for layoffs. CIOs need IT workers to have both the skill and the will to change. Transparent communication about the skills necessary for success and how skills audits guide personal development plans helps employees see a positive path forward. (Read more: Find Employees With Skills Promise to Drive Internal Mobility.)
CIOs should exercise extreme caution when collecting skills data and establishing metrics. Only collect data that leads to useful actions and regularly check if metrics are helping to drive the desired behaviors. By prioritizing transparency and privacy and focusing on data that’s relevant to business needs, employees will feel empowered to use their own data for growth. (Read more: Ten AI Value Metrics for Cost Reduction, Revenue Growth and Productivity.)
Step 3: Design the Human-AI Work Dynamic
CIOs who advance a narrative of human-AI equivalence will erode trust and credibility. Designing an AI-augmented organization requires CIOs to architect dynamic operating models that balance human and AI capabilities. The emergence of AI as more than a tool, but not a human equivalent, demands clear boundaries for AI autonomy, human agency, and accountability. (Read more: The Rise of the AI Toolmate: Defining AI’s Role in the Workforce.)
Quick start: Pick a common workflow and try one of these redesign approaches:
- AI-optimized: Rework the process to maximize end-to-end AI automation.
- Human-in-the-loop: Identify which steps AI can handle independently, which require human oversight, and which need direct human input.
Quick win: Redesign one workflow for AI by asking “how can AI do this?” for each step. To optimize for humans, start by defining which steps require human actions or decisions, which steps need human oversight, and when steps AI can handle autonomously.
CIOs will design the human-AI work dynamic by answering three critical questions:
1. How should we adapt our processes, team/org. structures, and career pathing models to optimize the value of a human + AI labor force?
AI will have a big impact on teaming and new functions will emerge specifically to harness AI’s potential. More than half of CIOs anticipate the rise of specialized teams, composed of both humans and AI, and new functions created to take advantage of AI (see Figure 4).13 (Read more: CIO Perspectives on the Future of Enterprise Functions in the Age of AI.)
Don’t just split up tasks — reimagine jobs so people can focus on work that truly matters. With AI at their side, workers can build automations, collaborate with AI “toolmates” for advice and creative ideas, and devote their energy to escalations and strategic decisions. This shift empowers your workforce to have greater impact and find more meaning in their work. (Read more: CIO Guide to Redesigning the Enterprise Architect Job in the Age of AI.)
2. How do we create a strategy, change management, and execution plan for various future-state scenarios of organizational design?
Avoid creating an AI “moral crumple zone,”14 where workers lose critical skills but retain all the liability. When passive oversight replaces active involvement, cognitive deskilling begins. Create a dynamic skills sensing network and co-lead with business executives in prioritizing the shift in jobs and skills needs, focus on improving workforce readiness through building enduring human capabilities in critical thinking, and problem solving (see Reference Guide for AI, People and Culture for more).
Change fatigue doesn’t signal resistance to change, it signals a failure with leading change effectively. Data shows that nearly 90% of workers are willing to adapt to changes, even at high frequency, if they trust how change has been handled in the past. Yet, only 21% of workers do.15 CIOs must help IT workers develop change reflexes, the core skills that help employees interpret and adjust to uncertainty. (Read more: Build IT Employees’ Resilience in Response to AI-Triggered Change.)
3. How do we balance agency, accountability, and innovation to ensure ethical, legal, and competitive outcomes in job redesign?
Developing better decision making autonomy for humans is a key priority for ensuring AI is used safely and effectively. CIOs must codify exactly when AI has agency (e.g., “autoapprove password resets for low-risk systems”) and when humans must make decisions (e.g., “approval for privileged access or critical infrastructure modifications”). (Read more: Predicts 2026: Intelligent Applications Shape the Future of Work.)
Process debt, skills gaps, and agility debt are now more urgent than tech debt. CIOs must develop “pro-skill-ity” to elevate the value contribution of each employee. When offloading tasks to AI, IT workers must be empowered to contribute to strategic and innovative solutions that contribute to growth.
Build a portfolio of future capabilities IT professionals will need as their jobs evolve with technology advancements. Craft multiple paths that enable them to develop those capabilities and build their capacity to lead in new domains. (Read more: A CIO’s Guide to Redesigning the Software Engineer Job in the Age of AI.)
Step 4: Scale Human Readiness for AI
CIOs must ensure that processes, governance, and teams can scale without losing alignment with strategic objectives or creating new risks. This requires embedding change management, feedback loops, and transparent performance measures. A cross-functional AI agent layer council (CIO, CHRO, CFO, COO, general counsel) is essential for scaling healthy use of agentic AI and an AI-augmented workforce.
Quick win: Scale your AI readiness by activating ambition. Run one AI mini-challenge a month aligned to a behavior, workflow, or business outcome with recognition for those who develop innovative ways of integrating AI.
CIOs will scale human readiness for AI by answering three critical questions:
1. How can I motivate employees to use AI tools to achieve better results?
Scaling AI successfully is 20% technology and 80% psychology. To ensure that employees feel safe and motivated to use AI, CIOs must address “AI shame,” both the reluctance to admit a lack of proficiency and the fear of judgment for using AI tools. (Read more: 2026 CIO New Year’s Resolutions — Three Workouts to Stay in Top Shape.)
“It takes a lot of hard work to make something look simple.”16 CIOs must shift incentives and recognition programs to reinforce AI-first behaviors. Implement a broad range of recognition programs to motivate AI fluency and influence IT workers to partner with key stakeholders on innovative AI solutions. (Read more: Why AI Initiatives Fail: A CIO’s Guide to Engaging Workers.)
Seventy-three percent of IT workers, and two-thirds of non-IT workers, use a personal Everyday AI tool for at least some of their work.17 CIOs must realize that shadow AI is not about rule-breaking; it’s a clear signal your AI enablement is too restrictive or that work provided AI tools are not sufficiently capable. CIOs must provide access to AI sandboxes protected by an adaptive governance model that applies risk-based guardrails. (Read more: Embrace Adaptive IT Governance to Accelerate Decision Making.)
— 2025 Gartner HR Symposium Preconference Survey81% of HR leaders report that legacy thinking is preventing leaders from supporting AI transformation.
2. How can I help managers lead teams that work well with both people and AI?
AI-augmentation for middle managers should focus on increasing span of value, not span of control. By equipping managers to augment their human strengths with AI tools, CIOs can free up time for higher-value, people-focused leadership. CIOs must deploy tailored learning pathways for managers that connect AI literacy to change-leadership skills like empathy, coaching, and emotional intelligence. (Read more: Leading Down: How CIOs Can Better Serve Their People Amid Rapid AI-Fueled Change.)
Don’t ask or tell; invite workers to co-create the future of work. Middle managers play a pivotal role in identifying use cases, managing resource interdependencies, monitoring for behavioral byproducts and modeling new ways of working. Managers should be trained on how to co-create job evolution with their teams, by equipping them with conversation guides and hands-on workshops. (Read more: Case Study: AI Adoption and Change Management Support for People Managers.)
3. How can I work with other executives to spread IT’s AI success across the whole organization?
Scaling AI for competitive advantage requires a bold, future-focused C-suite vanguard. CIOs must proactively engage executives in strategic conversations that showcase how IT’s AI achievements can be leveraged as catalysts for enterprisewide transformation. By positioning AI as a core driver of business strategy and value, CIOs can elevate IT’s importance to business outcomes. (Read more: How to Overcome Organizational Readiness Barriers for AI and Digital Success: CIO Perspectives, December 2025.)
Step 5: Evolve AI-Augmented Workforce Agility
AI-augmentation is not a closed loop; it demands constant iteration and signal sensing. In this final step, CIOs must ensure that a permanent feedback loop has been installed, to sense shifts in workflows, behavioral byproducts, and AI capabilities.
Quick win: Launch a weekly one-question AI pulse survey to gauge how AI is affecting employees’ work and well-being (e.g., what’s changing, what needs to change, what have they learned). Review responses in your cross-functional council and commit to one action each month based on feedback.
To maximize success in a highly volatile AI world, CIOs must be positioned to quickly double down and the discipline to divest. CIOs are ready to enact strategies for tomorrow’s needs by continuously revisiting assumptions, staying attuned to market signals, employee/customer feedback, and evolving business priorities. (Read more: Build human-machine Collaboration Curricula for AI Literacy Programs.)
CIOs ensure evolution by answering critical questions:
1. How should we update our EVP to attract and inspire top talent in an AI-driven workplace?
An EVP in the AI era requires the discipline of an “antistrategy,” which sets boundaries around what areas will not undergo AI transformation soon. This transparency and commitment mitigate AI fatigue and build the psychological safety necessary to attract talent who want to be on the leading edge of the future of work. (Read more: Mitigate AI Fatigue With Human-Centric Change Management.)
The IT manager’s role is to bridge the strategy-to-execution gap in organizations through the work their employees do. Equip managers with critical skills such as change advocacy, enabling them to identify and act upon opportunities for improvement, encourage prudent risk-taking, and mobilize their teams through times of constant change and uncertainty. (Read more: Use AI To Maximize The Value of Managers’ Work.)
“Stories constitute the single most powerful weapon in a leader’s arsenal.”17 CIOs must be able to paint a picture of how their vision for AI-augmentation benefits both the organization and the IT worker.
— Steven Wolk (CTO, PC Richardson & Son)¹⁸AI should be an augmenter, not a replacement. The goal is to give our people superpowers, not take away their purpose.
— David Williamson (ex CIO, Abzena)¹⁹AI will shift IT from being seen as a support function to being recognized as a strategic growth engine.
2. How can we tell if our key skills still match what we need for AI success?
Use adaptive change management to plan change iteratively. Use change sprints to responsively plan and implement AI initiatives. Adapt your change efforts by monitoring workforce signals showing willingness to change or where resistance to AI is undermining momentum. Organizations that adapt their change plans regularly or continuously based on employee response are nearly four-times (3.97 times) more likely to achieve change success.20
Benefit from failure by running collaborative sessions with cross-functional teams to review AI initiatives and analyze use cases and value signals to identify potential failures and go-forward approaches. Not only does failure build trust, it ensures the organization is better prepared for future challenges and that lessons learned are shared broadly (see Run Generative AI Failure Workshops to Raise Executive Risk Awareness for more).
3. How can we track if our human-AI teams are helping us achieve business results worldwide?
Effective sensing requires a multidimensional data strategy that captures both quantitative and qualitative signals. Workers leave behind a massive amount of digital exhaust, which, if gathered and interconnected effectively, can be turned into breadcrumbs that light up workflows. Common collaboration platforms like Microsoft 365 and Google Workspace, have built in sophisticated behavioral sensing hubs that can provide CIOs with real-time indicators of adoption and behaviors.
It has never been more critical to measuring the effectiveness of AI learning programs, but many organizations struggle to directly link AI learning programs to business outcomes. Ensure the ROI of AI learning programs by aligning metrics to achieve and improve business outcomes such as revenue growth, cost optimization, or competitive differentiation (see How to Measure the Effectiveness of AI Learning Programs for more).
CIOs must proactively navigate evolving AI data privacy and labor regulations across global markets. As AI matures, expect regulatory shifts and differing attitudes toward AI-augmentation. In China, data is viewed collectively, with policies favoring state interests and rapid AI adoption. In contrast, Europe and the U.S. emphasize individual privacy and enforce strict regulations.
Five Signals to Monitor as Your Human-AI Strategy Evolves
Capacity reallocation | Monitor how AI is helping you reallocate capacity by shifting routine tasks to AI and intentionally redeploy human capacity to higher-value work. | |
Emotional adaptation | Sense workforce engagement and sentiment to ensure teams are adapting well emotionally and remain motivated and confident in their roles alongside AI. | |
Work redesign | Assess how AI is leading to the creation of new jobs, workflows, and capabilities and their impact on strategic business outcomes. | |
Skills erosion | Regularly monitor and test for critical skills atrophy and experience starvation where junior workers lack opportunities to learn on the job. | |
Geographic implications | Partner with HR to continuously discover and adapt AI strategies to new and evolved AI regulations for AI data privacy and labor arbitrage. | |
Source: Gartner (January 2026)
Contributors
Tori Paulman, Shawn Murphy, Lily Mok, Brandon Germer, Kabeh Vaziri, Val Sribar, Helen Poitevin, Nate Suda
1 2024 Employee Perspectives on the Future of Work
2 2024 Gartner Digital Worker Survey
3 Gartner CIO Talent Planning for 2026 Survey
4 Gartner CIO Talent Planning for 2026 Survey
5 Gartner CIO Talent Planning for 2026 Survey
6 2025 Gartner C-Suite Dynamics Survey
7 2024 Gartner CIO and Technology Executive Survey
8 2023 Gartner Strengthening CxO Digital Leadership Survey
9 2024 Gartner Employee Perspectives on the Future of Work Survey
10 Gartner CIO Talent Planning for 2026 Survey
11 Gartner CIO Talent Planning for 2026 Survey
12 Gartner CIO Talent Planning for 2026 Survey
13 2025 Gartner CIO Leadership Forum Preconference Survey
14 Moral Crumple Zones: Cautionary Tales in Human-Robot Interaction, Madeleine Claire Elish
15 2024 Gartner Organization Structure and Leadership Trust Survey
16 Smithsonian Magazine, Steve Jobs
17 Forbes Howard Gardner
18 Harvey Nash, Steven Wolk (CTO, PC Richardson & Son)
19 Harvey Nash, David Williamson (ex CIO, Abzena)
20 2025 Gartner Foundations of Effective Organizational Change Management Survey