Hello, fellow humans! Today, we have some practical insights to help you empower your AI journey in 2026. Godspeed!

Retail and ecommerce teams using AI for customer service are resolving 40-60% more tickets without more staff, cutting cost-per-ticket by 30%+, and handling seasonal spikes 3x faster.

But here's what separates winners from everyone else: they started with the data, not the hype.

Gladly handles the predictable volume, FAQs, routing, returns, order status, while your team focuses on customers who need a human touch. The result? Better experiences. Lower costs. Real competitive advantage. Ready to see what's possible for your business?

See it in action

A new report from Intellum identifies a critical need for humans to adapt their skills in response to AI advancement. This includes developing "soft skills" like empathy, creativity, and critical thinking that complement AI capabilities rather than compete with them. The emphasis is on continuous learning and adaptability as core competencies for the AI era.

The four trends primarily impact enterprise learning and development (L&D) programs, so this may not be for everyone, but what happens in enterprise may filter to smaller organizations eventually, too.

AI Adoption Is Rising, But Bottlenecked By Readiness. Adoption is uneven and hindered by gaps in AI literacy, unclear implementation plans, and weak infrastructure

AI Can Only Accelerate Personalization With The Right Foundations. AI allows personalization at scale, but if you don’t have human architecture systems in place — skills language standardization, content metadata, and job structures.

The Human Side of L&D Becomes More Valuable. As this newsletter has been saying since the beginning, the most critical pieces in the AI era is the work that only humans can do: strategic/critical thinking, digital fluency, and leadership.

Career Mobility and Skills Strategy Will Become the New “Proof” of L&D Value. Identify mobility and skills metrics that can tell you how well your human skills are meeting the moment.

So while AI acceleration is changing organizational learning priorities, workforce adaptability is the new key competitive advantage.

We’re seeing AI agents become autonomous digital workers, and while that is transforming business operations, it’s having a massive effect in hiring and recruiting. These AI systems are moving beyond simple automation to become collaborative partners that can execute complex tasks independently while requiring new frameworks for governance and oversight. That might seem like a big win from a certain POV, but it represents a major hurdle for job-seekers and recruiters.

A new report from Redfield Press digs into the transition of AI agents from theoretical concepts to practical infrastructure in the recruiting space. In responding to the challenges and opportunities ahead for 2026, recruiting teams are shifting from role-filling to capability identification.

That means a greater emphasis on learning agility and adaptability in candidates, AI readiness as a critical hiring criterion, and highlights the need for people who can drive innovation and change.

Two reports from Harvard Business Review (HBR) complement each other; one tells a story of how we use AI, and another tells a story of the effects of those use cases. The research consistently shows that AI is transitioning from augmenting human capabilities to increasingly automating tasks. HBR's research on how people use AI reveals that directive conversations (automation) rose from 27% to 39% in just eight months at Anthropic, demonstrating this rapid evolution. However, this shift brings complex challenges - while AI collaboration increases productivity, it paradoxically reduces human motivation according to studies involving over 3,500 participants.

The Harvard report is built on a social listening data collection, so while the sample sizes are small, there are meaningful insights that cannot be accessed through other methods. And that’s what informs research about how we use AI, but when we pair that social listening data with observing real use, we can assess second-order effects.

Meanwhile, another HBR study of human behavior with gen AI shows that we experience big productivity boosts — more details, analysis, and content in less time — but over time proved to be demotivating. Gen AI users reported an 11% drop in motivation and a 20% increase in boredom.

The key insight is that successful AI integration requires a careful balance between leveraging AI's capabilities while maintaining human engagement and purpose. The behavior report offers 5 things you can do to stay fully engaged while still getting the benefits of gen AI.

Of course, we’re still in the early stages of the AI revolution, so none of this is written in stone. The more we use AI, the more we will discover about the technology and how we respond to it. So keep your head on a swivel out there.