What should IT leaders do when employees adopt AI tools faster than their organization can evaluate or approve them?

In this episode of AI at Work, I speak with Hemant Sahani, Vice President of Product Management for Workspace ONE at Omnissa, about the rapid growth of unsanctioned AI applications across the digital workplace.

Omnissa’s State of Digital Workspace 2026 research found that workplace use of AI assistant applications grew by nearly 1000% during 2025. Hemant describes this period as AI’s iPhone moment, with employees choosing the tools that help them work faster instead of waiting for an official corporate rollout.

We discuss why blocking every unapproved application can leave IT blind to what employees need. Hemant explains how observability can reveal where people are finding value, why approved tools may be falling short and which applications deserve a proper security, legal and procurement review.

Our conversation also examines Omnissa’s vision for the autonomous workspace. Hemant imagines an environment that can configure, secure and repair itself while identifying digital experience problems before employees need to raise a support ticket.

We also consider how AI is changing the responsibilities of enterprise IT. As device management, security and employee experience converge, IT teams increasingly need data skills, commercial awareness and closer relationships with HR, finance, security and legal teams.

Could shadow AI become a valuable source of workforce intelligence, and how should organizations balance employee freedom with their responsibility to protect company and customer data? Please share your thoughts with me.

Is artificial intelligence really eliminating entry-level jobs, or is something much bigger happening beneath the surface? As businesses race to improve productivity and invest in AI, many graduates and early-career professionals are wondering whether the first rung of the career ladder is quietly disappearing.

In this episode of AI at Work, I welcome Trent Cotton, Head of Talent Insights at iCIMS, for a data-driven conversation about how AI is changing hiring, workforce development, and the future of careers. Drawing on decades of HR experience and the latest workforce research, Trent separates headlines from reality and explains why the story is far more complex than many people assume.

We begin by examining one of the biggest concerns surrounding AI. Is the technology actually replacing entry-level jobs? Trent argues that the evidence tells a more nuanced story. Rather than AI directly removing roles, many organizations are redirecting investment toward AI infrastructure while failing to rethink how entry-level positions create long-term value. The result is a hiring market where junior candidates increasingly feel employers expect mid-level experience before offering someone their first opportunity.

Our conversation explores why that should concern every business leader. Entry-level employees don't simply fill today's vacancies. They become tomorrow's managers, specialists, and senior leaders. If organizations weaken that pipeline, they risk creating a leadership gap that may not become obvious for years.

We also discuss how AI presents an opportunity rather than simply a challenge. Instead of replacing early-career employees, Trent believes organizations should use AI to reduce repetitive work, accelerate learning, and shorten the time it takes for new hires to become productive contributors. That requires rethinking learning and development, coaching, and career progression instead of simply automating existing processes.

Another fascinating part of our discussion focuses on where technology talent is actually going. While many headlines concentrate on layoffs across large technology companies, Trent explains why skilled professionals are increasingly finding opportunities in healthcare, manufacturing, and other industries that are embracing AI to solve longstanding workforce shortages and operational challenges.

We also examine the skills that are becoming increasingly valuable regardless of how AI develops. Critical thinking, communication, sound judgment, and the ability to orchestrate people, processes, and technology remain difficult to automate. These capabilities, combined with technical literacy and continuous learning, are becoming the qualities that employers value most.

One of the biggest surprises from the conversation comes from changing attitudes among younger job seekers. Where previous generations often resisted assessments during the hiring process, many Gen Z candidates are now actively asking for opportunities to demonstrate their abilities through practical exercises rather than relying solely on a resume. As AI makes resumes easier to generate, proving genuine capability is becoming far more valuable than simply listing experience.

We also discuss responsible AI in recruitment and why governance cannot become an afterthought. Trent explains why organizations need clear policies, transparency, and accountability before introducing AI into hiring decisions if they hope to maintain trust with candidates and employees alike.

Is AI really closing the door on the next generation of workers, or is it giving businesses an opportunity to completely rethink how talent is developed? And as hiring continues to change, are we placing enough value on the human skills that technology still cannot replicate? I'd love to hear your thoughts after listening.

What if your business doesn't actually own its website, customer data, or digital marketing infrastructure? It's an uncomfortable question, but one that many founders never ask until they try to switch providers and discover just how difficult it is to leave.

In this episode of AI at Work, I welcome David V. Kimball, Co-Founder and CEO of lilAgents, for a conversation that challenges many of the assumptions businesses have made over the last decade about websites, software subscriptions, AI, and digital ownership. David argues that convenience often comes at a hidden cost, with businesses gradually handing control of their most valuable digital assets to platforms that make it increasingly difficult to move elsewhere.

We begin by exploring how so many organizations found themselves locked into ecosystems that seemed like the simplest option at the time. Website builders, ecommerce platforms, marketing suites, hosting providers, and CRM systems all promise convenience, yet many businesses only discover the downside when prices increase, features disappear, or they attempt to migrate to something better.

The conversation then turns to artificial intelligence and where it is genuinely making a difference today. Rather than focusing on AI chatbots that have been added to almost every product, David explains why AI agents are becoming far more interesting. These systems can perform real work, connect different applications, automate repetitive processes, and solve practical business problems while people focus on higher-value work.

One example that stood out involved a Shopify store with thousands of products that had accumulated years of inconsistent metadata. Using AI agents connected directly to Shopify's APIs, David was able to automate work that would have taken weeks by hand, helping improve search visibility and delivering measurable growth in organic revenue. It serves as a practical reminder that AI delivers the greatest value when solving real operational challenges rather than simply generating content.

We also spend time discussing the hidden costs many businesses overlook. From paying for CRM contacts that no longer engage to running websites on platforms with far more functionality than they actually need, David explains why simplifying technology stacks can often reduce costs while improving flexibility at the same time. The objective isn't simply spending less. It's building systems that businesses genuinely own and can adapt as their needs change.

Another theme running throughout our discussion is portability. Whether we're talking about websites, marketing platforms, AI models, or business data, David believes organizations should avoid becoming dependent on any single vendor. As AI continues to develop, he argues that businesses should think carefully about building modular systems that make it easy to change providers instead of finding themselves trapped by the next generation of platform lock-in.

This episode offers a refreshing perspective on AI by moving beyond the hype and focusing on practical outcomes. It also raises an important question about the future of digital business. Are companies investing in technology they truly control, or are they simply renting increasingly expensive pieces of someone else's platform?

How much of your digital business do you genuinely own today? And if one of your technology providers disappeared tomorrow, how easily could you move somewhere else? I'd love to hear your thoughts after listening.