Friday, May 9, 2025
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Hi, it’s Chad. Every Friday, I serve as your AI guide to help you navigate a rapidly evolving landscape, discern signals from noise and transform cutting-edge insights into practical leadership wisdom. Here’s what you need to know:
1. Paper Trail: AI Research Decoded
AI Citation Reliability: Practical Guidance for Business Users
Recent research reveals that (surprise!) AI research tools like ChatGPT, Claude, and Gemini can fabricate up to 60% of their references while systematically favoring prominent sources, requiring business users to implement verification protocols to harness their benefits while managing risks. Here are a few key Takeaways:
- Implement tiered verification protocols based on decision criticality – with higher stakes requiring more rigorous verification
- Expect domain-specific reliability differences, with technical and scientific information requiring more thorough verification than general business topics
- Combine AI efficiency with human verification in structured workflows to maximize benefits while minimizing risks Here are a few key insights:
Read our full analysis of each of these research papers at AI for the C Suite
2. Sound Waves: Podcast Highlights
Our latest episode featuring my conversation with Emily Tait, an Intellectual Property Partner with Jones Day at the forefront of AI’s legal frontier, is now live! Listen in as Emily and I discuss the misconception many creators have that simply providing input to AI means they own the output—and why that assumption isn’t legally sound. Subscribe for free today on your listening platform of choice to ensure you never miss a beat.
New episodes release every two weeks.
3. AI Buzz: Fresh Bytes
Here are several interesting articles that caught my eye. There were a few more than usual but, hey, it’s been an interesting week!
- OpenAI and the FDA Are Holding Talks About Using AI In Drug Evaluation
- When Does an AI Image Become Art? A Whitney Museum curator explains the history of art versus digital tech
- ChatGPT Enterprise – Models & Limits. Understand which models are best suited for your tasks
- Apple and Anthropic reportedly partner to build an AI coding platform
- Microsoft’s most capable new Phi 4 AI model rivals the performance of far larger systems
4. Algorithmic Musings. The Cost of Disruption: When Expertise Goes from High-Dollar to Free Lunch
In the very near future, clients of professional service firms will not continue to pay premium rates for services that AI can now provide faster and cheaper.
This idea bubbled up again this past week when I had the privilege of speaking about AI to a closed session of business leaders. During our panel discussion, my co-presenter surfaced this concept, highlighting how AI systems are rapidly becoming capable of performing tasks that traditionally required human expertise and specialized training.
This concept is an extension of how technology has historically reduced costs in other domains, yet is potentially more disruptive because it affects high-skill knowledge work that was previously thought to be resistant to automation. Since this is a concept which I haven’t previously unpacked for you, today is that day. Let’s explore the concept of how AI-driven democratization of expertise might affect a hypothetical business consulting firm, Morgan Strategy Partners (MSP), a mid-sized firm specializing in strategy consulting for retail businesses.
We begin with this question: What happens when the market value of MSP’s expertise plummets to near-zero?
Impact 1: When Your Secret Sauce Becomes Fast-Food Condiments
MSP currently charges premium rates ($300-500/hour) for strategy recommendations built on their consultants’ expertise and proprietary frameworks. It’s a model as old as consulting itself: “Pay us because we know what you don’t.”
But what happens when AI can provide comparable analysis and recommendations instantly at minimal cost?
Suddenly, clients start questioning MSP’s pricing model. The awkward conversations begin: “Why am I paying you $400 an hour when ChatGPT Plus costs me $20 a month?” The firm faces immense pressure to either dramatically reduce fees or justify value beyond what AI alone can provide.
That exclusive expertise in retail strategy? It’s transforming from a premium service into a commodity faster than you can say “digital disruption.”
Impact 2: Flip the Organizational Pyramid
MSP adapts by integrating AI systems internally. This is where things get interesting.
Junior associates, armed with the right AI tools, can suddenly perform at levels previously requiring 10+ years of experience. That associate who graduated three years ago? With AI augmentation, she’s now capable of work that previously required a senior consultant with an MBA and a decade of experience.
This enables the firm to restructure its entire workforce pyramid. They reduce reliance on expensive senior consultants while empowering junior staff with AI-augmented capabilities. Project timelines shrink from months to weeks, and operational costs drop significantly.
Stop and think about this for a moment. We’re not talking about AI replacing humans – we’re talking about AI democratizing expertise within organizations. It’s like giving everyone in your company a wise mentor who’s available 24/7.
Impact 3: From Selling Expertise to Orchestrating It
Recognizing this fundamental shift, MSP transforms from selling expertise directly to becoming an “expertise orchestration” company.
Their value proposition shifts from “we know the answers” to “we help you understand and implement the answers AI already knows.” They focus on the human elements that remain challenging for AI: change management, implementation support, and navigating organizational politics.
They develop a platform combining industry-specific AI models with human oversight, providing clients ongoing access to continuously updated expertise rather than point-in-time consulting projects.
To riff on Bob Dylan’s famous lyrics: the times they aren’t just a-changin’, they’ve already changed while most of us were busy making other plans.
Questions to Ask Yourself
If you lead or work in an expertise-based business, consider these three questions:
- What aspects of your expertise are most vulnerable to AI commodification?
- How might you restructure your organization to leverage AI-augmented junior talent?
- If your current pricing model collapsed, what new value could you provide that AI can’t?
The expertise apocalypse isn’t coming – it’s already here. Some firms will dance with this disruption, while others will get trampled by it. The difference will be in who sees it coming and adapts first.
Got questions about how AI might impact your business model? Drop me a line and let’s figure out if you need to lace up your dancing shoes or invest in some running gear.
5. Elevate Your Leadership with AI for the C Suite
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As we navigate this unprecedented fusion of human and machine intelligence, remember: the best leaders aren’t just adapting to change – they’re actively shaping it. Until next week, keep pushing boundaries.
Chad