Rochana Golani, VP of Enablement at Databricks, is one of the most innovative and business-focused learning executives I’ve met. In this action-packed conversation Rochana shares the secrets of the company’s AI-powered dynamic training, learning, and enablement system, and how she runs internal and customer learning like a fast-growing business. Databricks is one of the world’s fastest-growing enterprise software companies and a central player in the convergence of data infrastructure, analytics, machine learning, and generative AI. Founded in 2013 by the UC Berkeley researchers who created Apache Spark, Databricks pioneered the “lakehouse”—an architecture designed to combine the scalability of a data lake with the management, reliability, and analytical capabilities of a data warehouse. Its platform now supports data engineering, business intelligence, AI development, governance, databases, and enterprise AI agents across AWS, Microsoft Azure, and Google Cloud. Databricks company overview This amazing private company reports: More than 20,000 customers Approximately 70% of...

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Workday’s Q2 2027 earnings were a pivot point, showing how Workday has shifted to its “AI-Forward Future.” The company reported $600 Million of recurring AI revenue and a clear and confident position in the market. While Workday’s 12.8% YTY revenue growth is nowhere near that of a Frontier Lab, my takeaway is that Workday is here to stay and has a clear position in the agentic business ahead. Listen up and you may agree with me that SaaS software companies are not going away at all: they may form the basis for the enterprise AI wave ahead. Additional Information Introducing HR 2030: A Vision For Agentic Human Resources Workday Reports Higher Profit, Revenue on AI Agent Adoption Galileo: All our Research and Much Much More

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Today I review the various jailbreaks by both OpenAI and Anthropic and the challenges which Frontier Labs are having with AI “alignment.” So in keeping with HR 2030, I share some general advice and stay tuned for our detailed technical paper on this in the coming weeks. And as we debate the reliability, training, and alignment of models I also point out how the technology industry is struggling to deal with the politics and economics here, since right now most tech leaders really don’t want any form of regulation. (Unless it’s somehow fair to all.) So we, as buyers, are left dealing with the issue. AI Alignment means making sure an AI system’s goals and behavior match what people actually want—our values, rules, and intentions. It’s about getting the AI to do the “right thing” even in new situations, not just follow instructions literally in ways that cause harm. In...

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Today I share some research we’re doing on wages in the inflationary “AI-economy.” While many people are studying the labor market (it’s a huge industry), it’s not hard to see that most wages are not keeping up with inflation, yet some are. As you’ll hear we now see the “Superworker” jobs and roles that are “inflation protected” and we also see the jobs that are declining in value. I also discuss a new pragmatic approach to corporate AI investment, as well as the slow end of the “SaaSpocalypse” idea. In other words, many of the existing systems you have are not going to be “destroyed” or “replaced” by agentic disruptors: rather these software companies are becoming AI savvy. This includes Workday, Oracle, ADP, SAP, as well as hypergrowth companies like HiBob. Even Docebo and Cornerstone are now seeing the benefits of their AI pivots. Anyway lots to talk about, and...

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I have spent almost 30 years studying organizations, work, jobs, and HR, and every year there’s a new theme. There was digital transformation, employee wellbeing, hybrid work, diversity and inclusion, women’s rights, and now AI. What’s the real direction here? One might argue that employment and jobs are becoming “more human,” but that’s not true. Today companies lay people off continuously with no more than an email and 4 hours notice. We abandoned DEI and topics like pay equity are almost a joke (new AI engineers make $500,000 or more). And now that CEOs talk about AI increasing “productivity” employees are more worried than ever. In fact one trend that I see is a steady, 30+ year decline in trust. Every study from Pew to Edelman shows a decline in trust between workers and their bosses. In 2024 PwC found that only 67% of employees trust their employers overall and...

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This week I wade into a global philosophical debate about whether advanced AI systems have consciousness. In other words, are they aware of their feelings and do they truly reflect on their own thoughts? Well we do know that LLM-based AI systems do “talk to themselves,” as new Anthropic has been studying in the J-Space. We also know that AI bots mimic feelings quite well and they try to tape into our “feelings” through their goal-seeking language which mimics a feeling person. However as Michael Pollen’s book “A World Appears” points out, consciousness is both subtle and biological. And while the neural network-based math in AI mimics this process, it’s not at all the same. I don’t claim to have an answer but my belief is that we humans are “feeling machines that learn to reason” not “reasoning machines that learn to feel.” Thus the human consciousness which we experience...

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