Another Crazy Day in AI: How to Integrate Humans and AI Without Organizational Chaos
- Wowza Team
- Sep 2
- 4 min read
Hello, AI Enthusiasts.
Some days, it feels like every corner of tech is moving at once. Today’s no different.
With years of experience deploying AI in enterprise settings, David Boskovic has seen firsthand how the technology performs when the stakes are high. Flatfile, his company, works with sensitive business data that leaves no room for error. He suggests that AI adoption isn’t simply about doing work faster but about deciding which roles belong to humans versus machines.
Meanwhile, AI is also rewriting how new medicines move from lab to clinic, slashing development time and raising the possibility of replacing animal testing with smarter models.
Then there’s shopping... Amazon has rolled out a camera-powered feature that lets you scan your surroundings, match products instantly, and add them to your cart in real time.
Here's another crazy day in AI:
The Human-AI collaboration handbook for leaders
Biotechs adopt AI as FDA shifts away from animal testing
Amazon adds real-time scanning with Lens Live
Some AI tools to try out
TODAY'S FEATURED ITEM: Enterprise Guide to Human-AI Team Building
Image Credit: Wowza (created with Ideogram)
What if the biggest AI transformation isn't about making humans better at their jobs, but completely reimagining what jobs should look like?
SaaStr’s Founder, Jason Lemkin, shares a deep dive from David Boskovic, the founder and CEO of Flatfile, who has spent years deploying AI agents for Fortune 500 companies in highly sensitive data environments. His insights come from hundreds of enterprise AI deployments, and his company works with mission-critical business data where mistakes aren't an option, giving him a front-row seat to how AI actually performs in real enterprise environments.
Boskovic argues that the way AI is being implemented today isn’t just about efficiency or productivity gains—it’s about redesigning the roles we expect humans and machines to play. In his view, many traditional tasks and functions may be better suited for AI agents entirely, which raises broader questions about the future of work and how companies can structure themselves to fully leverage these tools.
Here are some of the perspectives he puts forward:
Three common AI integration approaches and why two of them consistently underperform in enterprise settings
Economic parallels from the space industry where cost reductions of this magnitude created entirely new markets
A content team case study demonstrating how roles evolved when AI handled execution while humans focused on direction and quality
Three new organizational positions including operational specialists who bridge the gap between AI capability and business implementation
Practical deployment challenges such as model inconsistency and the timing gap between technical readiness and organizational capacity
The evolving value of different skill sets as routine work becomes automated and judgment-based work becomes premium
Employee adaptation observations from multiple Fortune 500 rollouts showing who thrives and who struggles
Boskovic brings a practical perspective that's often missing from AI workplace discussions. He's dealing with these challenges from two angles: helping enterprise clients implement AI solutions while also trying to scale his own company using these tools. This dual experience gives him insight into both the sales promises and the operational realities. Rather than promoting a particular methodology, he documents what he's observed across different organizations, including the strategies that don't work as advertised.
His observations feel particularly relevant because they're based on current implementations rather than theoretical frameworks or future predictions. Boskovic acknowledges that everyone is figuring this out as they go, which makes his specific examples more valuable than broad generalizations about AI's workplace impact. The piece captures the experimental nature of what's happening right now in enterprise environments, where companies are testing different approaches to integrating AI tools while managing the organizational complexities that come with significant workflow changes. His willingness to discuss both successes and failures provides a more complete picture of what these workplace transformations actually look like in practice.
Read the full blog post here.
OTHER INTERESTING AI HIGHLIGHTS:
Biotechs Adopt AI as FDA Shifts Away from Animal Testing
/Sneha S K and Puyaan Singh, Correspondents, on Reuters
AI is rapidly reshaping drug discovery as the FDA pushes for reduced reliance on animal testing. Biotechs like Schrodinger, Recursion, and Certara are already using AI to predict absorption, toxicity, and safety, with some drug candidates moving to clinical testing in half the usual time. Experts say timelines and costs could shrink by more than 50% within five years, though animal testing is unlikely to disappear completely. The FDA envisions AI-driven tools and human-cell models as the new standard in pre-clinical testing.
Read more here.
Amazon Adds Real-Time Scanning with Lens Live
/Trishul Chilimbi, Vice President and Distinguished Scientist, Stores Foundational AI, on Amazon Newsroom
Amazon has launched Lens Live, an AI-powered feature in its shopping app that enables instant product scanning and real-time matches. Customers can now pan their cameras across items to see swipeable results, tap for details, or add products directly to their cart without leaving the camera view. Integrated with Amazon’s AI assistant Rufus, Lens Live also provides quick product insights and answers questions on the spot. The feature is now available to tens of millions of iOS users in the U.S., with broader rollout planned.
Read more here.
SOME AI TOOLS TO TRY OUT:
That’s a wrap on today’s Almost Daily craziness.
Catch us almost every day—almost! 😉
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