Earlier this month, I attended the SaaStr event for software-as-a-service providers. The event is geared toward smaller SaaS companies that want to share ideas to learn how to scale and grow.
The biggest company, by far, in attendance was IBM Corp. I was surprised to see it there, given the show’s focus on smaller SaaS providers, so I talked to Raj Datta (pictured), vice president for software and AI partnerships, about IBM’s presence at the show.
He told me IBM was there to support and cultivate independent software vendor partners. IBM’s booth wasn’t the typical everything-IBM stand, but rather a “IBM Partner Plus” flavor of a booth. The purpose of its presence was to facilitate relationships and enable partners to build AI solutions on watsonx.
I spent some time there talking to other IBMers and their partners. Here are my top takeaways:
AI has moved from vision to reality
Industry watchers and media continue to talk about AI as a future technology, but the reality is that AI is here, and it’s creating new experiences. At SaaStr, I met two IBM partners, both of which have solutions built on watsonx.
TruGolf is a golf simulator that uses watsonx to generate AI commentary. As one walks up to the golf ball, the system will greet the player, comment on history, and then comment on the shot taken.
Another IBM partner, Geminos, uses watsonx for what the company calls “causal AI,” where it looks at the data to find the “cause and effect” of the analysis done. This can be particularly useful in understanding why AI hallucinations occur. These are just two examples of the many companies building with watsonx, indicating we are in the reality phase of AI. It’s time for companies to stop thinking about AI and start doing it.
Success with AI requires an ecosystem approach
No company can successfully deliver AI alone, as there are too many moving parts to consider, many of which are not purely technology. I spoke to Datta about this, and he told me, “As you know, companies are adopting our technology, and one way we can help them is by closing the skills gap. We have a large engineering organization, particularly compared to the smaller SaaS vendors. We help our partners build out the technology, and then once it goes live, we have a partner ecosystem that does everything from joint marketing to helping them learn how to sell the technology better.”
Historically, IBM has been known for its large software partners. With AI, it is also building an ecosystem of smaller ISVs — where much of the AI innovation will come from.
Guardrails are necessary but complicated
For all the good that AI promises, there are concerns about the “dark side” of AI, which stems from bias, hallucinations and other issues. In my conversation with Datta, he said, “Ethical concerns continue to be a huge barrier for companies because of not having governance models. We’ve heard about how AI has spit out biases and has spit out incorrect information. This is an area that IBM continues to invest in on behalf of our customers.”
For in-house projects and smaller ISVs, I encourage them to rely on the big AI providers such as IBM, as they have the necessary expertise and technology to tackle these issues, which can be very expensive and time-consuming.
AI reskilling is a must
AI is set to replace tens of millions of jobs. The exact number is anyone’s guess, but I’ve seen estimates as low as 10 million and as high as 300 million.
On the surface, this looks like bad news, but it’s excellent news, as AI will create far more jobs than it displaces. Also, AI will enable us to work smarter and faster. The key today is to help workers reskill to prepare themselves for the next wave of technology.
This job transition happened with the rise of the internet, the growth of the cloud, and the evolution from mainframes, and it will be with AI. In 2022, IBM revamped its approach to skilling, offering partners access to the same training and enablement as IBMers.
Additionally, Datta told me, IBM has hired thousands of engineers to help ISVs embed AI into their software. The premise is that the ISV understands its software, customer and product roadmap. IBM engineers can augment their skills with theirs to deliver a joint solution.
Build solutions that solve a specific enterprise pain point
There are almost infinite possibilities of problems that AI could solve; the question is where to start. As an example, Datta shared a data point that 91% of those who are unsatisfied with a brand will leave, which isn’t a shock. I have similar data that shows two-thirds of millennials leave a brand because of one bad experience or that 90% of companies now compete on CX.
So that begs the question: How can I fix the problem? Datta shared a follow-up data point that found that 51% of agents without AI spend most of their time on mundane tasks. AI can fix that problem by automating the mundane, enabling agents to spend more time engaging with customers. He showed similar advantages for finance, talent management, operations and more. The lesson is to start with the big problem and then use AI to solve the areas with the most human latency.
SaaStr is in the books, and as expected, AI was the top theme of the show. AI will be the biggest technology change agent since the rise of the Internet, but several challenges must be overcome first. Smaller ISVs should rely on bigger partners such as IBM, not just for technology but also for skills, marketing and other support.
