Beware the Miss
This Week in Enterprise Tech, Episode 21 tackles AI governance (well, sort of), Anthropic's unusual investment in benchmarks, and why data center power consumption is top-of-mind again.
👋 Hi and welcome to The DX Report — the research hub of The DX Institute all about Digital Transformation, the Digital Experience, and the Digital Enterprise. I’m industry analyst, author, and speaker Charles Araujo, and I’m all about providing insights and analysis for enterprise IT leaders as you make the big bets about your organization’s future!
What are you missing?
I've been doing a lot of work recently with SymphonyAI's Enterprise IT division on messaging around its new Copilot offering. One of the things I've been telling the leadership team is that one of its super powers is the ability to help enterprise IT leaders catch the thing they may have otherwise missed.
The need to identify those potential misses was one of the earliest lessons I learned from a mentor CIO at the very beginning of my career.
I called her on a Saturday unsure if I should have bothered her about an issue that I felt could cause significant issues come Monday if we were unable to resolve it.
She assured me that I should ALWAYS call. She explained that she'd rather give the executive team a heads up about something that might happen and then explain that we rallied and resolved it rather than have to explain, after the fact, why something went terribly wrong.
Her greatest risk and fear was the miss.
Not much has changed.
The never-ending and constantly growing complexity of the enterprise IT tech stack continues to challenge even the most disciplined IT organization. How great would it be, then, to have an AI-powered assistant that you can ask to help identify anything that you might be missing, right?
The Risk of the AI Governance Miss
But I digress.
There are lots of potential gotchas lying around the floor of the modern IT organization. But one of the biggest is likely the issue around AI governance.
I've been talking about the need to address it for a while, so I was encouraged when I saw a recent CIO article on the topic. Unfortunately, the article was mostly a nothing burger suggesting that all you need to do is leverage existing data and corporate governance policies and approaches.
I think this is a big potential miss.
AI governance is going to be exponentially more difficult to address because of its widespread impact and its shear breadth.
And I don't think there's a clear cut approach to it — at least not yet.
Hyoun and I dove into this subject a bit this week. But the big message is beware what you don't know or what you think you know, but don't!
Happy listening!
🗓️ This Week in Enterprise Tech, Episode 21
In a holiday-shortened week, Charles Araujo of the DX Report and Hyoun Park of Amalgam Insights still found some critical topics for enterprise IT leaders. We cover Anthropic's funding the development of new AI benchmarks, why CIOs are recklessly underestimating AI governance needs, and how AI power costs are becoming materially important for upcoming CIO budget forecasts.
Segment descriptions and links to all the articles we discuss are in the Show Notes, below.
Watch the full episode here:
Or listen to the episode here: https://www.buzzsprout.com/2319034/15383552
📔 Show Notes
[01:20] Anthropic to Fund New AI Benchmarks
Anthropic recently announced its intentions to both develop and fund new benchmarks that more accurately describe the behavior and performance of Large Language Models (LLMs). Charles and Hyoun discuss why this is a good move from Anthropic in terms of the needs for better benchmarks, an enhanced understanding of generative AI, as well as Anthropic's own self-interest in standing out from OpenAI and other large AI competitors.
[08:15] CIOs Recklessly Underestimating AI Governance Needs
A recent article from CIO.com kicked off a discussion between Hyoun Park and Charles Araujo on the massive chasm between the current discussions in AI governance and the reality of the breadth of AI governance challenges that CIOs seem poorly prepared for. It is not enough to just lean on legacy data governance policies and a decade of cloud computing experience. CIOs need to look across the challenges of data, model development, model training, talent management, infrastructure management, power management, and environmental concerns.
CIO.com: https://www.cio.com/article/2510265/4-essential-lessons-in-ai-governance.html
[17:27] AI Power Costs Enter CIO Budget Forecasts
A firm called Phaidra got Hyoun and Charles' attention in tackling the challenges of data center power management. After a decade of CIOs thinking that they had built their last data center, the cost of unmanaged cloud and the challenges of AI are starting to force CIOs to reconsider their on-premises IT strategies. In a world where data center infrastructure management is making a comeback and practically every large enterprise is now a hybrid multi-cloud ecosystem, CIOs will be forced to take a broader role in translating electricity, power, and utilities into digital outcomes.
TechCrunch: https://techcrunch.com/2024/07/02/phaidras-ai-helps-manage-data-center-energy-consumption/
Venture Beat: https://venturebeat.com/ai/will-the-cost-of-scaling-infrastructure-limit-ais-potential/