Today we’re speaking with Sofia Khaira, a leading specialist in diversity, equity, and inclusion whose work focuses on helping businesses navigate the complexities of talent management in an era of rapid technological change. As our go-to HR expert, she provides critical insights into creating work environments that are not only inclusive but also resilient and future-ready.
In our conversation, Sofia delves into the immense pressure on C-suite leaders to demonstrate tangible financial returns from artificial intelligence, moving beyond simple headcount reduction. We explore the delicate process companies are undertaking to decide which roles to automate and how they are managing the human impact of these decisions. Sofia also unpacks the central paradox facing today’s leaders: balancing widespread layoffs driven by economic uncertainty with the critical need to upskill existing employees and attract scarce, highly-skilled talent. Finally, we touch on the strategic alignment between CEOs and HR leaders on AI, and where that partnership often encounters friction during the critical execution phase.
The SHRM survey found AI adoption is a higher priority for 2026 than growing revenue. What specific financial results are CEOs under pressure to show from AI, and could you walk me through an example of how an AI initiative translates into tangible value beyond simple cost-cutting?
The pressure is enormous, and it’s shifted from a theoretical “we should be using AI” to a very real demand from boards and investors to see a clear return. They want to see how AI is fundamentally improving the business, not just shrinking it. For instance, think of a global logistics company. Instead of just using AI to automate scheduling and reduce administrative staff, a more valuable application is deploying a predictive analytics model. This AI could analyze weather patterns, port congestion, and geopolitical shifts in real-time to reroute shipments proactively. The tangible value isn’t just a few saved salaries; it’s millions of dollars saved by avoiding delays, reducing fuel consumption, and guaranteeing on-time delivery, which in turn strengthens client relationships and secures larger contracts. That’s the kind of value creation executives are now expected to deliver.
With a Resume.org survey showing 37% of employers expect to shed jobs via AI by 2026, how are companies deciding which roles to automate? Please describe the step-by-step process leaders use to identify these positions and manage the internal communications around these sensitive changes.
It’s a process that has to be handled with incredible care, and the smartest organizations are approaching it systematically. It typically begins with a comprehensive audit of all roles and tasks within the company, identifying which are highly repetitive, rule-based, and data-heavy—those are the prime candidates for automation. From there, leaders map this against their future strategic goals. The crucial next step, and where many falter, is communication. You can’t just announce that a department is being automated. The narrative has to be about evolving the business to remain competitive and creating new, higher-value opportunities. This means being transparent weeks, if not months, in advance, and immediately presenting a clear plan for the affected employees, whether it’s robust severance, outplacement services, or, ideally, a direct pathway into a reskilling program for a different role within the company.
Given that 75% of CEOs anticipate more layoffs while also struggling to find skilled talent, how are leaders practically balancing this with Johnny Taylor’s call to invest in upskilling? Can you share a real-world example of a company successfully reskilling employees whose roles were at risk?
This is the tightrope every leader is walking right now. It feels contradictory, but it’s about surgically removing roles that no longer serve the future business while simultaneously investing in the people who can build that future. A great example I’ve seen is in the financial services industry. A major bank identified that hundreds of its mortgage processing roles were becoming redundant due to new AI-powered platforms. Instead of a mass layoff, they launched an internal “Future Skills Academy.” They offered these processors fully-paid training and certifications in high-demand areas like cybersecurity analysis and data privacy management—fields critical to the bank’s future. While some employees chose to leave, a significant portion transitioned into these new, more secure roles. It was a clear demonstration of investing in their own people first, which directly addresses the talent scarcity problem and builds incredible loyalty.
The article mentions that economic uncertainty from factors like inflation makes planning difficult. How do these external economic pressures complicate a company’s AI implementation strategy? For instance, how does an organization decide whether to attribute a layoff to AI efficiency or to broader economic headwinds?
Economic uncertainty acts as a massive brake pedal on bold AI initiatives. When capital is expensive and consumer demand is unpredictable, a multi-million dollar investment in an unproven AI system feels incredibly risky. Leaders become more cautious, favoring smaller, quicker-win projects over large-scale transformation. When it comes to layoffs, the attribution is almost always blended. It’s rare for a company to issue a press release saying, “We are laying off 500 people because our new algorithm is more efficient.” Instead, the narrative is framed around broader economic challenges. They’ll cite the need to become more agile and efficient in a tough market, and leveraging technology like AI is presented as one of the tools for achieving that resilience. This makes the decision feel like a prudent response to external forces rather than a cold, technological replacement of human workers.
Your research shows a “good amount of alignment” between CEOs and CHROs on AI. In your experience, where does this alignment typically break down when moving from strategy to execution? Please provide some anecdotes on the common friction points that emerge between the C-suite and HR leaders.
The alignment is fantastic on the 30,000-foot view. Both the CEO and CHRO agree that AI is critical for the future. The friction starts the moment the plan hits the ground. A classic friction point is the timeline. I worked with a tech company where the CEO, fresh from a conference, wanted to implement an AI-driven performance management system and restructure the sales team based on its outputs within a single quarter to show immediate efficiency gains. The CHRO had to step in and show data on how a rushed, poorly communicated rollout would likely trigger top-performer resignations, destroy team morale, and result in a net productivity loss for the next two quarters. The CHRO’s job becomes translating the CEO’s strategic urgency into a human-centered execution plan that doesn’t break the organization in the process. This is where the strategic alignment often meets the messy reality of managing people through change.
What is your forecast for the relationship between AI and the human workforce over the next five years?
My forecast is one of turbulent, but ultimately positive, transformation. The next two to three years will continue to be disruptive, with more restructuring and job displacement as companies sort out which AI applications truly deliver value. However, I believe we are nearing a peak in the “AI as a job killer” narrative. The focus will increasingly shift toward human-machine collaboration. The companies that thrive will be those that stop seeing this as a zero-sum game. They will excel at identifying how AI can augment their employees’ skills—handling the mundane, analyzing massive datasets—freeing up humans to focus on strategy, creativity, and complex problem-solving. The most valuable employee of 2030 won’t be a data scientist, but a ‘synthesizer’—someone who can work seamlessly with AI tools to derive insights and lead teams in this new environment.
