AI News
03 Feb 2026
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How CIOs and CHROs collaborate on AI to boost productivity
how CIOs and CHROs collaborate on AI to streamline hiring, upskill staff, and boost productivity now.
Want a quick view of how CIOs and CHROs collaborate on AI to raise productivity without losing the human touch? Start with shared guardrails, clear use cases, and a joint skills plan. Lessons from Pearson, Intuit, West Monroe, and Ralliant show how to deploy agentic tools, measure results, and scale what works.
Leaders are racing to use AI to boost results, but adoption is uneven. Many workers still say they never use AI. That is why alignment between tech and people leaders now matters most. When both sides agree on what to automate, where humans stay in control, and how to upskill, change sticks. This is where how CIOs and CHROs collaborate on AI becomes the lever for real productivity.
Productivity gains and reduced workflow friction
Speed to market for new products
Employee engagement and AI adoption
Growth of new skills
Chief Technology and Growth Officer Amir Kazmi pushes a “learn-by-doing” culture, even for senior leaders. He notes that agentic AI is still early, so humility and experimentation are key.
Write a clear automation policy: define “can, should, shouldn’t.” Keep humans in final control for hiring and other sensitive calls.
Give broad access to core AI tools, then focus on 2–3 high-friction workflows where AI can show quick wins.
Co-build a skills map tied to the tech roadmap. Blend upskilling with selective hiring at critical intersections.
Redesign recruiting and team-formation steps. Use chatbots to speed matching and reduce bias.
Form cross-functional councils to share playbooks and align on standards and security.
Measure outcomes, not activity: throughput, cycle time, quality, customer impact, adoption, and skills growth.
Adopt agentic AI with oversight. Set review loops so humans validate outputs and agents check one another when useful.
Start small, document lessons, and scale the patterns that work.
Strong results come when tech and people leaders move in sync. The stories above show how CIOs and CHROs collaborate on AI to protect human work, speed delivery, and grow skills. Start with guardrails, pick clear use cases, measure impact, and keep learning. That is how CIOs and CHROs collaborate on AI to boost productivity—and keep trust high as the tools evolve.
(Source: https://fortune.com/2026/01/28/how-cios-and-chros-are-working-together-to-reimagine-work-as-ai-tools-proliferate/)
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How CIOs and CHROs collaborate on AI: A practical playbook
Agree on what to automate—and what never to automate
Pearson’s CHRO Ali Bebo and CTO Dave Treat work from a simple rule: protect human moments. They ask if tech should automate a task and when it should not. They deployed “Cara,” a chatbot that answers career and skills questions. They may use agentic AI for light coaching, but managers still lead. One hard line: AI will not make final hiring decisions. Clear guardrails build trust and speed adoption.License widely, target deeply
Pearson gave every employee a Microsoft Copilot license. That sets a baseline for daily use. Then they focused on high-impact cases. In customer service, Salesforce AI agents now handle 63% of cases. The lesson: spread access, then double down where AI unlocks speed and quality.Build skills maps and pipelines together
At Intuit, CTO Alex Balazs and Chief People and Places Officer Caryl Hilliard co-own a skills roadmap. They decide which skills to grow in-house and when to hire. They compete for talent at the AI–software edge, but they also invest in entry-level hires. Gen Z engineers arrive with strong CS skills and AI coding tools. Intuit runs a multi-week boot camp to build collaboration and team skills. The tech roadmap shapes learning; the people team shapes the path to mastery.Redesign the hire-to-retire journey with automation
West Monroe’s Chief People Officer Tanya Moore and CIO Kevin Rooney rebuilt workflows across the employee lifecycle. Automation now handles scheduling and recruiting tasks equal to three full-time employees. A new tool that streamlines interview feedback is set to save $1.5 million a year. They also built an internal chatbot to help resource managers form project teams. It asks for needed skills and assembles candidates fast. It also reduces bias by widening the talent pool beyond the usual contacts.Create cross-functional councils and measure what matters
Ralliant formed working group councils that include tech and people leaders. These groups share use cases and spread best practices. The team tracks:What the data says about adoption and AI agents
Surveys show a mixed picture. Gallup reports that AI use has been flat lately, and nearly half of U.S. workers say they never use AI. Leaders use AI more than managers and individual contributors. Still, big companies remain optimistic. KPMG finds two-thirds would keep AI spending even in a recession, with average 2026 budgets of $124 million. Agentic AI is rising fast: 26% of firms have deployed it, up from 11% a year ago. And 44% of leaders expect AI agents will manage parts of projects alongside humans in the next two to three years. Open questions remain. How many agents can one person direct? How should humans review agent work? When should agents review other agents? Testing will reveal the right balance.Action checklist for CIO–CHRO AI partnerships
Use this list to structure how CIOs and CHROs collaborate on AI and move from pilots to scale.FAQ
Q: What are the first steps organizations should take to implement AI across HR and IT?
A: Begin with shared guardrails, clear use cases, and a joint skills plan so both tech and people teams agree on what to automate and what to keep human. That approach reflects how CIOs and CHROs collaborate on AI to raise productivity while protecting human moments.
Q: How do leaders decide which tasks AI should never automate?
A: Teams should evaluate whether automation would undermine human connection and set explicit lines for sensitive decisions, as Pearson’s CHRO and CTO do when thinking about human-plus-machine tradeoffs. For example, Pearson’s leaders agreed AI will not make final hiring decisions to preserve human oversight.
Q: What licensing and deployment strategy increases AI adoption in an enterprise?
A: Give broad access to core AI tools and then concentrate on a few high-impact workflows; Pearson provided every employee a Microsoft Copilot license and targeted customer service with Salesforce AI agents. That targeted approach helped Pearson reach a point where agentic AI handles 63% of customer service cases.
Q: How should technology and people leaders coordinate hiring and skills development for AI work?
A: Co-build a skills roadmap to decide which capabilities to grow in-house and when to hire externally, as Intuit’s CTO and people leader do to align talent with the tech roadmap. Intuit also emphasizes entry-level hires and runs a multi-week onboarding boot camp to combine Gen Z engineers’ CS fundamentals with collaboration and team skills.
Q: In what ways can chatbots speed recruiting and reduce bias?
A: Internal chatbots can automate coordination and screening, as West Monroe’s tool helps resource managers form project teams by asking clarifying questions about needed skills. Moore and Rooney say the bot speeds team assembly, widens the candidate pool to reduce bias, and automation across scheduling and recruiting now handles work equivalent to three full-time employees.
Q: What governance structures help ensure responsible AI adoption?
A: A clear automation policy that defines “can, should, shouldn’t” and keeps humans in final control for hiring is essential, and cross-functional councils help align standards, security, and best practices. These governance elements are central to how CIOs and CHROs collaborate on AI and set the review loops needed for agentic systems.
Q: Which metrics should organizations track to measure AI’s impact on work?
A: Track outcomes like throughput, cycle time, quality, customer impact, adoption rates, and skills growth rather than just activity levels. Ralliant also measures productivity, reduced workflow friction, speed to market, and employee engagement to evaluate AI initiatives.
Q: How should companies approach adopting agentic AI and experimentation?
A: Treat agentic AI as an early-stage capability and encourage a learn-by-doing culture while starting small, documenting lessons, and scaling what works, as Ralliant’s leaders recommend. Adopt agentic tools with oversight and review loops so humans validate outputs and agents can check one another when useful.
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