Looking at AI from Multiple Enterprise POVs
Looking at AI from Multiple Enterprise POVs
This Week in Enterprise Tech, Episode 7, was all about AI (and it's a bit late!). But the critical point of discussion is how to look at it from various perspectives as an enterprise IT leader.
👋 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!
Another week, another episode of This Week in Enterprise Tech, the podcast I produce with Hyoun Park, CEO of Amalgam Insights.
Publishing note: Travel, a freak April snowstorm, and some power outages conspired to make this episode a little late. Sorry!
But rather than simply summarizing the podcast and providing links as I’ve been doing, I’ve decided that I’m going to provide a little more meat on the bones for you as a subscriber to The DX Report. Beginning with this episode, I’m going to give you a little analysis of what I think the news of the week means in the broader context for you as an enterprise IT leader or industry follower. My hope is that it will help you digest our discussion more readily and help you put things into action.
So here goes.
AI is All Around
The big take away from this week’s news is that it is impossible to avoid AI.
Before we recorded, Hyoun and I asked ourselves if there was perhaps some non-AI news we had missed. The short answer: no!
AI is dominating the news because it is the big game changer in virtually every domain. Of course, that doesn’t mean it’s dominating your day-to-day existence. I’m quite confident that it’s barely registering.
But it should be dominating your strategic planning cycles because it is now the driving force behind most transformative actions.
The trick will be to maintain balance and context.
Making AI Practical, Defensible, and Sustainable
Balance and context will be all important when it comes to doing your real job when it comes to AI: making it practical, defensible, and sustainable for your organization.
We led off our discussion talking about Databrick’s somewhat surprising release of a quasi open sourced LLM that it claims it developed in only a few months for $10MM. The promise, of course, is that the company can help you do the same — building a proprietary LLM using your own data at a reasonable cost and timeframe. If it lives up to its promise (and hype), that’s a solid pathway to creating practical competitive advantage from generative AI.
Along these same lines, we discussed two Wall Street Journal articles covering some of the first efforts to calculate ROI from these efforts — no easy feat yet — and how some organizations are applying generative AI to streamline and supercharge their supply chains. The big takeaway here is that there are some short-term wins to be had if you focus appropriately and don’t get caught up in the big, sweeping elements of the AI story and, instead, focus on the immediate business value you can create using this technology.
In the end, that’s always the story with any tech and any transformation effort: there is a direct correlation between your focus on business value (and organizational change/adoption) and the success of your efforts.
Finally, we stepped back and talked a bit about the emerging “AI wars” between NVIDIA and everyone, and between Microsoft and OpenAI on one side and AWS and Anthropic on the other — and the bets you may (or may not) need to make. And we talked a little bit about the lessons you can take from the government’s recent AI mandates: yes, you need to be aware of the risks and take concrete steps to mitigate them, but you also had better be looking at the opportunities to leverage this tech to create competitive advantage.
As always, there was a lot to cover, but these are essential topics that you need to get into to remain relevant as an enterprise IT leader. Enjoy the episode!
This Week in Enterprise Tech, Episode 7
This Week in Enterprise Tech? More like This Week in Enterprise AI as your intrepid heroes Hyoun Park from Amalgam Insights and Charles Araujo from the DX Report analyze AI products from multiple startups, AI value mapping challenges, a new alliance taking on NVIDIA, and the United States' Government's new policies on AI and what they mean for enterprise CIOs.
Segment descriptions and links to all the articles we discuss are below in the show Notes.
Watch the full episode here:
Show Notes
1. Databricks DBRX Gen AI Model. Databricks unleashed a 132 billion parameter open source model developed in 3 months on a $10 million budget based on a Mixture-of-Experts approach that exceeds other open source models in performance while providing greater speed and compute efficiency. Find out why MoE is the new RAG in Gen AI and why we found this so surprising.
Databricks' announcement https://www.databricks.com/blog/announcing-dbrx-new-standard-efficient-open-source-customizable-llms
Additional commentary from Techcrunch: https://techcrunch.com/2024/03/27/databricks-spent-10m-on-a-generative-ai-model-that-still-cant-beat-gpt-4/
2. Hume AI's "Empathic AI." Hume AI announces a $50 million B round to support "Empathic AI". Charles and Hyoun debate the efficiacy of pursuing empathic AI based on previous approaches from startups such as Kanjoya and Textio and some of the hurdles and challenges associated with an empathy-based standard of AI for the enterprise.
For more on the funding announcement: https://www.hume.ai/blog/series-b-evi-announcement
3. The Practical Business Value of Gen AI. Hyoun and Charles saw a couple of pieces in the Wall Street Journal this week on the ROI of AI as well as the use of AI in supply chain through established vendors such as Celonis. We discuss what key metrics and ratios CIOs should consider in the value of AI and how to align AI to practical business outcomes.
The WSJ takes on ROI in AI: https://www.wsj.com/articles/cfos-tackle-thorny-calculus-on-gen-ai-whats-the-return-on-investment-24ebf435
And the WSJ take on AI and supply chain: https://www.wsj.com/articles/companies-are-seeking-real-world-supply-chain-gains-in-new-ai-tools-023045e7?mod=djemCIO
4. NVIDIA vs. the World in AI. A new consortium including Amazon is seeking to unseat NVIDIA's dominance in AI. Will it succeed? And what does it mean for CIOs seeking to place their bets on AI?
Based on the following Reuters article: https://www.reuters.com/technology/behind-plot-break-nvidias-grip-ai-by-targeting-software-2024-03-25/?taid=6601616d9876060001c70b64
And the following WSJ article: https://www.wsj.com/tech/ai/amazon-invests-2-75-billion-in-ai-startup-anthropic-87bb869e?mod=djemCIO
5. US Government Takes a Stance on AI. We saw a two-for-one this week from the US government as the executive branch announced a policy to require every agency to define AI safeguards and have an AI head. And in the legislative branch, the staffers of the House of Representatives have banned Microsoft CoPilot for now. What lessons can enterprise IT take from Government-grade Gen AI?
White House Fact Sheet on AI govermance: https://www.whitehouse.gov/briefing-room/statements-releases/2024/03/28/fact-sheet-vice-president-harris-announces-omb-policy-to-advance-governance-innovation-and-risk-management-in-federal-agencies-use-of-artificial-intelligence/
Axios breaking the story on the US House banning the use of CoPilot: https://www.axios.com/2024/03/29/congress-house-strict-ban-microsoft-copilot-staffers