An entire workflow can sit idle because nobody has noticed that one step has finished and the next can begin. Someone in your workflow needs to research, compile, organize, draft, tabulate, and complete any number of laborious tasks requiring hyperfocus and… time.
A healthcare AI system can do exactly what it was built to do and still leave a care team with more work. Flagging a change between appointments may help a patient receive care sooner, but it also creates a review task for someone already caring for other patients.
Earlier this year, I wrote that browser automation was a bridge period. At the time, my focus was trust. Agents could technically complete workflows, but the systems around them were not really designed to know who was behind the request, what the agent was authorized to do, or whether the interaction should be trusted. I still think that is true.
In June, the U.S. Department of Health and Human Services announced that more than one billion health records had been exchanged through TEFCA, the national interoperability network. The volume grew from 10 million to more than one billion in less than a year. Healthcare is developing the infrastructure required to exchange information across the system at a scale we have not seen before.
Voice AI’s next executive benchmark is inbound ability, because the voice is the interface, but the workflow is the value. I’ve written before that voice AI’s missing piece is the ability to listen while it talks. That’s still true. A voice agent that can speak back is no longer the interesting benchmark. The more useful question is what happens after somebody starts talking.
In April, the Linux Foundation announced that the A2A Protocol, an open standard for AI agents to talk to each other across platforms, had passed 150 organizations and was already seeing production use in its first year. That tells me something important about where the enterprise AI market is going.
When I look at what happened with UnitedHealthcare’s Change Healthcare unit, I think it shows the problem very clearly. Change sits in the middle of an enormous volume of U.S. medical claims, so when a cyberattack hits, it does not stay contained.
I think a lot of people look at AI agents and assume the bottleneck is technical. Better APIs. Better infrastructure. Better models. Better compute. But I don't think that is the real thing holding this back.
As autonomous AI gains momentum, the same technology that threatens networks could be their best defense.
Most companies I talk to are already using AI. They just do not know it yet. It looks like a junior employee with a “quick question” who ends up dumping PDFs, documents, agreements, and sometimes Excel files into ChatGPT or Grok.
A decision made at speed by an agentic system cannot be unmade at speed by a human. It’s a mismatch that is reshaping what leadership accountability means and undercutting the value of executive experience, because these systems operate in conditions no one has seen before.
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While America retrofits legacy infrastructure, India and Saudi Arabia are building from scratch.
Companies are planning AI-driven workforce cuts faster than they are deploying AI itself. According to McKinsey’s 2025 workplace survey, 32% of organizations expect to reduce their workforce due to AI within the next year, yet most haven’t scaled AI enterprise-wide.
America needs strong, prosperous allies to maintain markets for our technological leadership in AI development and deployment. But right now, our allies (especially in Europe) are struggling industrially and our traditional response is inadequate.
For all the billions poured into AI deployments, the project attrition rate has been extraordinary.For all the billions poured into AI deployments, the project attrition rate has been extraordinary.
When Nvidia convinced the White House to sell downgraded chips to China, critics warned it would undermine U.S. security and erode our AI advantage. In reality, it was a win-win, driving growth in both countries while protecting America’s technological lead.
Here’s the brutal math of the labor transition facing the American workforce: It takes 30 days for a 25-year-old AI-native college graduate to become productive. Meanwhile, I have employees with 20 years of experience who struggle to shift from their comfort zone to master the new tools.
In the debate about the impact of automation and agentic AI on the American workforce, there are two camps: those sounding the alarm on massive job displacement and those who want to know which specific roles will be eliminated. The difference is stark. Vague warnings will likely only lead to panic and bad policy responses. But, as a country, if we know which jobs are at risk, we can prepare, retrain, and adapt.
When Chinese AI startup DeepSeek launched its R1 model requiring far less computational power than their American peers in January, it was only exposing the limitations Silicon Valley had already begun acknowledging.
As digital transformation becomes even more multidimensional—with hyperautomation coming on stream and AI agents reshaping business operations—the nature of outsourcing is changing rapidly, too.
Business leaders are not the only ones to have experienced bootstrapping their way up only to find themselves struggling to scale.
The old outsourcing dilemma of build versus buy is already a time capsule of the recent past. In its 2024 survey of 500 global executives on talent sourcing, Deloitte found that digital transformation and the pace of emerging technologies are forcing organizations to rethink how they source and manage capabilities.
When leaders tell employees that automation will free them up for “higher-value work,” often strategic, we must be careful not to sidestep a more complex reality. The transformation to hyperautomation
LEAP 2025, the world’s largest tech event, kicked off with a record-breaking $14.9 billion USD in new technology investment announcements for the Kingdom of Saudi Arabia.
After the party, the hangover. In the wake of the Great Resignation, Great Regret, Great Reset, and Great Return, the zeitgeist has shifted. Remember when Google let
There’s a myth going around that digital natives have short attention spans. Anyone who believes this has obviously never watched an eSport gamer be consumed by tactics and strategies in the immersive world of virtual competition.
Mercer predicts there will be a nationwide healthcare worker shortage of 100,000 by 2028
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Solid business relationships are the bedrock of organizations destined to succeed. They are intangible assets and harbingers of better things to come in the future. They do, however, require a fair amount of effort.
Fear is not to be feared. My mantra is, "Embrace it." Fear is natural. We're wired for it. It keeps us from a myriad of dangers. And we're not the only ones — nearly all living things contain some sort of self-defense mechanism.
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