Are You Living in the Eye of the Hype Cycle?
This Week in Enterprise Tech, Episode 20, serves as a framework to effective strategic planning by reading the tea leaves and employing the Gretzky model of strategic planning.
👋 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!
Forgive my mixed metaphors, but I think they are apt, given our situation. There is no question that the bombardment of AI-everything for the past year and a half has put us smack in the middle of an accelerated hype cycle.
But I also think that we can look at all of this as a crazy storm — one in which we find ourselves right smack in the eye.
The thing about being in the eye of a storm — especially when it's a big one — is that you don't really know what's going on. You think you can see clearly, but you may not be able to see the tumult swirling just out of sight.
There is no question that AI — generative AI, specifically — is going through the traditional, albeit accelerated, hype cycle. But while the hype cycle is typically a linear affair, this one is going to act more like a dynamic, constantly shifting, and hard to predict storm system. The unpredictability factor is made all that more challenging by the fact that we're in the middle of it all.
So, whether you're an enterprise IT leader of the leader of an enterprise software company, the question is the same: how do you develop a cohesive go-forward strategy in this swirling mess?
Reading the Tea Leaves
This week's episode of This Week in Enterprise Tech serves as a bit of a framework to answer that question.
To continue my pursuit of leaving no metaphor disabused, the key is to get good at reading the tea leaves.
The actual process of tea leaf reading is, of course, bogus. But the idea that we can look to small things for hints to the future is a useful metaphor — and essentially what we do each week on the podcast.
This week, we covered how many of the recent funding rounds for enterprise software companies are for what Hyoun called bridge technologies — tech that fills in the gaps left by other, more established tech. Whether it's solutions to deploy workflow automation to close business process gaps, solutions to simplify enterprise search, or tools to enable organizations to leverage multiple AI models, there are plenty of gaps to be filled.
We also covered the march toward the operationalization of AI. Anthropic and OpenAI took wildly different approaches (a new interface and some key acquisitions, respectively), but both moved in the direction of making their foundational AI models more usable on a day-to-day basis. Likewise, we covered some new research from Together.ai that proposed what it calls long inference models and a mixture-of-agent approach to simultaneously reduce the cost and increase the speed of generative AI — another key part of the operationalization process.
Finally, we covered a piece by MIT professor Rodney Brooks cautioning against overly rosy expectations and a piece in the Wall Street Journal that made clear that reality as CIOs grapple with making AI deliver results in the real world.
As you think about your go-forward strategy, the question is what does all of this tell you?
Using Signals to Create Informed Strategic Alignment
There's a common misconception that a solid strategy is one that has successfully predicted the future. But that's not it. Instead, a winning strategy is one that can read these tea leaves to directionally understand where things are headed and then align the investments and actions to that direction. You can call this the Wayne Gretzky approach to strategy: skate to where the puck is going to be.
The trick is, Gretzky wasn't using some divine insight to know where it was going to be, he was watching everything happening — the signals — and using that information to figure it out.
That's was the secret to his greatness and almost every success story ever written. It's no different here.
We're all sitting in the middle of this chaotic, constantly changing, AI-powered storm. At moments, it may seem clear and obvious. But the truth lies deeper. You need to find the signals and put them all together to really see what's happening and where the opportunities may emerge and the risks may lie.
That's what Hyoun and I try to help you do each week. Happy listening!
🗓️ This Week in Enterprise Tech, Episode 20
This week, Charles Araujo of The DX Institute and Hyoun Park of Amalgam Insights cover the wide-ranging news of the week, including the current investing climate for enterprise software companies, the move toward AI operationalization, and the limits of generative AI along with some new approaches that may make it faster and cheaper.
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/2319034/15345536
📔 Show Notes
[00:59] Emergence Seeks to Bridge All the Agents
Emergence recently came out of stealth raising over 90 million in capital as well as access to 100 million in debt to manage agents. It’s first product is an agent orchestrator that can bring workflows and models together, which speaks to a feature when we will all need to coordinate multiple agents in the workplace
https://techcrunch.com/2024/06/24/emergence-thinks-it-can-crack-the-ai-agent-code/
[05:00] Can Creatio Bridge CRM + Workflow Automation?
Creatio just raised $200 million to take on the twin problems of CRM and workflow automation. Their approach involves bringing best in breed applications together to support a united Voltron of CRM suite functionality.
[08:20] Zoho Blueprint Bridges Automation Gaps
Zoho has expanded its Blueprint capability over time to support management, document management, and document signing capabilities. We quickly discuss what it means to expand automation across an application suite
[09:56] Hebbia Bridges Documents for Search
Hebbia is taking on an interesting role in supporting search across multiple documents. This allows it to bridge some of the capabilities of LLM’s and of traditional search. We discuss whether this is a matter of being stuck in the middle or bridging important gaps.
[14:40] Perplexity and Anthropic Face Legal Challenges
LLM‘s continue to run into legal challenges and requests to desist in its current data collection activities. The most important thing here is to try to not use LLM‘s that are currently facing legal challenges in the particular activities that you were using the LLM for.
[15:27] OpenAI and Anthropic Chase After AI Collaboration
Open AI has been on an acquisition streak over the past week, purchasing both database company Rockset and collaboration company Multi. We couldn’t help but see a trend as Anthropic has developed Artifacts to continue AI-based work in a separate window
https://openai.com/index/openai-acquires-rockset/
https://www.anthropic.com/news/claude-3-5-sonnet
[21:54] MIT Pioneer Rodney Brooks Side-Eyes AI
iRobot cofounder Rodney Brooks has been tracking AI a long time and prescribes caution for enterprise IT organizations currently working on generative AI projects. Although we are bullish on generative as a whole, we are glad to see this voice of restraint from a long time AI practitioner and professor
[28:09] Mixture-of-Agents Can Supersede ChatGPT, for now
We recently ran into this interesting Medium post by Ignacio de Gregorio that goes over the mixture of agents approach, which is showing superiority over top performing LLM‘s. By using A layered architecture of prioritized models, primary research is finding that models can actually make up for each other’s weaknesses and provide better answers when used in combination.
https://medium.com/@ignacio.de.gregorio.noblejas/mixture-of-agents-beats-chatgpt-4o-6470a74f1525
[33:15] AI Agent Studio Pursues Agent Governance
We took a quick look at how Automation Anywhere is preparing businesses for the future of agent governance with its AI agent studio
[35:25] AI Assistants Need a Work Buddy
This article by Isabelle Bousquette at the Wall Street Journal shows that out of the box agents are still struggling to handle business challenges. This isn’t a big surprise given the past decade of enterprise history with AI, but it is still a warning that generative AI is not simply a matter of finding the right model and hoping you can set it and forget it.