Today’s read is 878 words and a 3:53 minute read.
Our job is to keep our finger on the pulse of what’s happening with Talent in the Age of AI.
Here are some little “hits” of what I’ve been reading lately. To read even more and access FREE resources, see TalentintheAgeofAI.com.
Wendy Wiseman
Okay, we’re in. Now how do we legislate use?
Acceptance of AI in the workplace is growing – no doubt about that. In fact, McLean & Company’s 2025 HR Trends Report says that while 42% of HR leaders engage with AI technology, only 7% have a formal, documented strategy, highlighting a significant gap between AI use and strategic governance.
This is indicative of how technology changes often land in the lap of the HR department, and well they should. I attended a workshop with an attorney versed in AI who said that there is a ton to consider in the employment sphere, and sidenote: emojis in documents can denote a legal agreement.
Human-in-the-Loop Mandate
A cornerstone of HR AI policies is to never let AI make the final output alone. Some companies are documenting specific intervention points where a human must sign off on the content, particularly with hiring and performance reviews. Other companies are establishing “permitted use” tiers, like Low Risk: general brainstorming, drafting internal emails, summarizing non-sensitive meeting transcripts, Medium Risk: data analysis re: anonymous employee information, and High Risk: Putting in personally identifiable info. Additional policies center on Data Privacy and Leakage Prevention, addressing the Trust Gap via transparency, and AI audits.
| Talent in the Age of AI interviews forerunners in this area to provide context and lessons learned. |
Also in the report, it appears that recruitment has shifted as a top priority, replaced by leader development and employee retention. As AI accelerates, leaders need to focus on growth and purpose, with 73% recognizing the need for significant skill changes for the future of work, like those who know how to leverage AI toward company goals and productivity.
Brings to mind our podcast interview with Maiven Collective, a company centered on helping women increase their adoption of AI at work, as they lag men in this today.
My take: Accept that AI Use policies are needed, and they may have to evolve every six months to keep up.
– McLean’s 2025 HR Trends Report
One-size-fits-all AI models aren’t for all after all.
While we’re just in February, it appears a shift happening now is one away from LMM to SLM as organizations are realizing that they need more manageable output. In fact, the article I read leads with a headline: Failure Surfaces with General-Purpose Models in Production. Most systems were built in the Large Language Model (LMM) and they’ve become the defaults components for teams.
Small Language Models (SLMs) existed alongside this shift, mostly out of focus. They were trained or tuned for specific tasks, with explicit limits on what they were expected to do. These narrower models are no longer peripheral. They are increasingly where real design decisions are being made.
Leaders are increasingly adopting specialized “Small AI” solutions over massive “all-in-one” models leading to cost reduction, superior task performance, operational reliability, privacy, and security.
My take: Precision and the measurable ROI of AI implementations is a good thing. Refinement is getting us there.
– LinkedIn Strategic Insights, January 22, 2026
Is AI the bad guy, or the person sitting next to you?
About 43% of workers across generations are worried that another employee with better skills in generative AI could replace them in their role in the next year: 52% of Gen Z workers appear to be most worried with 45% of millennials and 33% of Generation X workers feeling the same.
It’s a confidence thing, and a permissions thing. Employees need to know it’s okay to deploy AI in their jobs (albeit with company policy as discussed above). Sasha Thackaberry, vice president of Wave at D2L, put it this way: “Skills development — whether it’s on using AI more efficiently or simply upskilling to stay ahead of change — is crucial for workers to keep up with the rapidly changing landscape of work.”
This should drive a modified training curriculum. Here’s some motivation:
In a survey of 3,000 full-time and part-time U.S. employees, 60% said they want to use AI more frequently at work. About 49% said they’re already using AI at least once a week at work, and 52% said they’re using the tools outside of work. At the same time, 37% said they never use AI tools.
If you can give them this training at work, it would go a long way: Younger workers were more likely to say they plan to take multiple professional development courses during the next year. About 26% of Gen Z workers and 24% of millennials said they plan to enroll in 6-10 courses in the next 12 months, as compared with 12% of Gen X workers. Think of it as a perk for them, prep for your workforce.
My Take: Reach across the generations – and the genders – to instill confidence and relevant use of AI to move your company forward.
– D2L February 12, 2026 report.