One Giant Leap?
After last week’s biotech update, it only seems fair to do the same with the other half of the Palumbo Emerging Growth Portfolio. This week we provide an update on the Portfolio’s emerging technology side, which includes in AI, robotics, and Web 3.0. The comments below reference discussions with Marc Weiss, Co-Founder and CIO of Open Field Capital, as well as comments made by several AI software vendors and analysts. The bottom line is that it appears broader adoption of AI is taking hold and is generating valuable results for end users.
AI Adoption: Seeing Traction on the Front Lines
We are now reading about successful stories from the ‘front lines’ of companies working with software vendors and consultants to take over failed in-house efforts and beginning to realize real value from AI projects. Success stories from such vendors as Salesforce, Service Now and Palantir, indicate that companies are actually beginning to realize return on investment from their AI efforts, including service enhancements and productivity improvements. Innovative approaches to AI implementation, using AI agents and “agentic workflows,” which are terms creeping into the discussion on AI, are substantially improving the accuracy of the outcomes for users.
These software companies have been able to package their AI capabilities with these “AI agents” along with new chips and hardware services to make AI cost effective for early adopters. We expect a ramp up in adoption based on these early successes.
The success Salesforce (CRM) is having using agents appears to be based on Marc Benioff’s comments on the company’s August 28th, 2024, Earnings Call. Marc spoke of their client experience with their AI capabilities platform, “Agentforce.” “The accuracy of our results, the reduction of the hallucinations and the level of capability of AI is unlike anything I think that any of us have ever seen…” He went on to predict “by the beginning of our next fiscal year, we will have thousands of customers using this platform.”
In a report dated September 29, 2024, Stifel software analyst, J. Parker Lane, said the following:
After digesting what we’ve seen and heard around AI agents from applications software providers over the past month, we’re left with the age-old question, “What if it really is different this time?” It’s no secret that software companies are typically heavy on marketing hype while customers and investors are left twiddling their thumbs in anticipation of realizing the value of innovative solutions or watching a once intriguing solution die on the vine. So, when we say “different,” we mean that the hype is matched with real life substance, real life use-cases, and real-life revenue.
With the launch of Agents at their respective conferences in mid-September, we think Salesforce and HubSpot have taken significant steps forward in their respective AI journeys and are driving towards a scenario where they’re less dependent on the seat-based model that they built their businesses on. While we are not calling for a complete replacement of employees by AI agents and believe AI copilots/assistants continue to serve an important purpose within organizations, we believe Salesforce’s Agentforce and HubSpot’s Breeze Agents have the potential to play both defense and offense for each company as AI proliferation continues.
Software Will Be Where the AI Rubber Hits the Road
The early beneficiaries of the most recent technological waves started with hardware vendors. The AI era has started on the same pathway and is driven by hardware providers, specifically chip companies such as NVIDIA (NVDA) and AMD (AMD). However, as in previous cycles, the largest and most sustainable commercial success of AI will typically be driven by those that can use the hardware most efficiently. This suggests that the value-added benefits in AI implementation will broaden from the hardware companies, such as NVIDIA and expand to those that can use the hardware to make it work.
Industry experts suggest the next, and potentially larger phase will benefit the software providers, providing services such training and inference for AI implementation. The key to this success is generating positive experiences with users at an acceptable cost. This cements AI as an increasingly indispensable tool for corporations in their daily operations, and validating AI as an emerging technology megatrend with the potential to generate the long-term capital gains for savvy investors.
The Evolution of AI
The launch of ChatGPT started the generative AI wave in earnest. AI had been around in the background, but the generative aspect of ChatGPT opened up an entire range of new possibilities/potentialities for this innovative technology. The hyperscalers, such as META (META), Google (GOOGL), and Amazon (AMZN), were forced to invest heavily if they wanted to stay in the game and that led to the massive acquisition of NVIDIA chips to keep pace.
Similar to the introduction of client server technologies in the early 1990s, everyone felt they had to “be in it to win it”. Since the Chat GPT introduction, NVIDIA has been the massive beneficiary of that demand surge with the stock rising exponentially over that time.
But it’s never as easy as it looks. The early Large Language Models (LLMs) were interesting, but certainly not ready for prime time. The rise of Chat GPT changed that dynamic and drove a frenzy to buy AI chips with the hyperscalers buying up everything in sight, driving AI adoption costs materially higher.
AI implementation also became an issue. Companies lucky enough to get chips were confronted by a dearth of available talent to implement AI as the limited talent pool gravitated to the hyperscalers. With a shortage of knowledgeable professionals, companies’ internal efforts and implementation periods went from weeks to months and beyond, with these projects largely failing to gain traction.
Stories about AI implementation included its ridiculous expense as well as outcomes with no value. The word on the street began to say much of the AI story was hype. Many investors were feeling the hyperscalers might never see an adequate return on their investment.
But LLM models have quickly become more accurate, and hallucinations (errors) began to decline. Software companies that already had in-house talent began using it for their business and found it valuable. Then they began generating “AI services” and including tools such as AI agents and agentic workflow to substantively improve outcomes. They began soliciting their corporate clients to help them garner the same benefits. Concurrently, newer technologies have sprung up with faster hardware speeds and lower costs.
The belief here is that the AI revolution is beginning to generate success with users, which can lead to the broad adoption of AI in business processes. The result could be one of the most impactful technology megatrends we have seen, with the potential to offer attractive long-term opportunities for capital growth.
In concert with our research advisors, we stand ready to entertain questions regarding the Palumbo Emerging Growth Portfolio and its AI related holdings as well as the exciting potential opportunities we see, so please feel free to reach out to us!
Have an enjoyable week!
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All information has been obtained from sources believed to be reliable, but its accuracy is not guaranteed. There is no representation or warranty as to the current accuracy, reliability, or completeness of, nor liability for, decisions based on such information, and it should not be relied on as such.
The views expressed in this commentary are subject to change based on the market and other conditions. These documents may contain certain statements that may be deemed forward‐looking statements. Please note that any such statements are not guarantees of any future performance, and actual results or developments may differ materially from those projected. Any projections, market outlooks, or estimates are based upon certain assumptions and should not be construed as indicative of actual events that will occur.
Past performance is no guarantee of future returns.
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AI, Artificial Intelligence, hyperscalers, software, TechnologyBy: Adam