#brian solis

The real question in the AI-and-jobs debate isn't "Will AI take jobs?" — it's where, how fast, and for whom. Brian Solis unpacks Anthropic CEO Dario Amodei's warnings that roughly 50% of entry-level white-collar jobs could be disrupted within one to five years, then moves past the headline to examine Anthropic's new labor market report and its concept of "observed exposure" — a measure that weights not just what AI could do, but what it's already being used to do at work. Roles like computer programmer (75% task coverage), customer service rep (70%), and financial analyst (57%) top the exposure list, while 30% of workers show zero coverage at all — a reminder that the disruption will be uneven and threshold-based, not universal.

The early warning signal Solis highlights isn't mass layoffs — it's the career ladder. Anthropic's data shows a 14% drop in job-finding rates for workers aged 22–25 in highly exposed occupations since ChatGPT's launch, a pattern that doesn't appear for workers over 25. Critically, the most-exposed group skews more credentialed and more female, making this a white-collar, knowledge-work story — not a "low-skill" one. Solis's bottom line: leaders who wait for unemployment data to confirm disruption are already too late. The smarter move is redesigning entry-level roles and apprenticeship paths now, treating AI as an operating model change rather than a headline to debate.

Why it matters for communicators: The story you tell about AI inside your organization will either prepare people to adapt or prime them to panic — and right now, most internal narratives are stuck on the wrong question.

AI will not automatically produce innovation just by helping organizations move faster; without a “mindshift,” most teams end up using AI to scale yesterday’s work rather than create new value. Brian Solis describes a “fork in the road” between iteration (measurable efficiency and optimization) and innovation (reimagining what value you create), warning that if AI is only used to automate existing tasks, it accelerates the past instead of transforming the business.​

Solis says change efforts often fail because people can’t see themselves on the other side of transformation—leaders talk vision while employees hear disruption, replaceability, or loss—so transformation spreads through meaning, not logic alone. He frames “I don’t have time” as a leadership signal about priorities and belief systems, suggests filtering AI noise by looking for signals with momentum, convergence, consequence, and context, and proposes practical moves like an iteration/innovation test and a “no workslop” standard where AI-generated output must be edited and improved before sharing.​

Why it matters: If leaders don’t pair AI rollout with clear meaning, role clarity, and higher quality standards, employees will interpret “AI adoption” as speed-up or replacement—and that narrative will undermine trust and change readiness.

As the world develops, new generations emerge, such as Generation Novel. Jacob Chacko, Regional Director – Middle East, Saudi & South Africa at Aruba, a Hewlett Packard Enterprise company, tells us about Gen N and their impact on digital experiences.     The impact of the pandemic might have varied widely between individuals but a few certain aspects of largely been universal – lockdown,…

Seth Godin on The Massie Effect. You know that feeling that you're feeling like in the minority for believing in social, climate, or institutional progress? You aren't as alone as you think.

Brian Solis on Are Bots Coming For Your Job? Yes. Brian outlines a future with more "human centered innovation", but corporations barely support their staff's creativity and innovation now. All the metrics, are geared towards revenue and productivity. I don't see them moving away from that without Government or Shareholder intervention. Do you need a Job, Career, or Calling? Based on AI gunning for most jobs, might be a good idea to look for your calling. Callings are more resilient to changes in markets and technology.

The Quietus on The Oral History of Warp's Artificial Intelligence Compilation. 1992? It sounds as relevant now as ever...but then Autechre was always ahead of their time.