If you aren’t supporting your clients’ generative AI initiatives, your competition surely is. Two-thirds of businesses are relying on MSPs for gen AI support, according to ISG’s recent Market Lens GenAI Use Case Study. The main factors pushing business executives to hire MSPs for this purpose include knowledge acquisition, speed, and limited in-house capabilities.
This data indicates an opportunity for MSPs; supporting your clients’ AI initiatives can not only offer a new revenue stream, but also increases your likelihood of onboarding new logos by offering that “shiny new ball” so many SMBs are currently interested in. Here are some of the most important takeaways of the study—and how you can apply them to your MSP.
What Are Clients Looking For In Generative AI?
The study found that customers are most commonly using Gen AI for customer service chatbots, IT testing, and content generation, both written and visual. But in terms of which areas businesses are prioritizing for next year, the results shift slightly. Customer service and chatbot support come to the very top of the list, followed by business process, workflow management support, and market research.
Alex Bakker, ISG distinguished analyst and co-author of the study, which surveyed executives with decision-making power in G2000 businesses, points out that large language models (LLMs) have primarily “been aimed at supporting humans who have capacity issues. [Things like] chatbots and customer support are fundamentally capacity limited. You’re trying to help them do the existing service faster. That’s useful, but it doesn’t really scale beyond the people who are fronting those processes.”
However, Bakker says the research indicates a shift coming. “If you look at what [the businesses have indicated interest in] for next year, it’s market research, supply chain optimization, planning, and forecasting, and cogeneration. These are expertise scaling problems. You probably are not limited because you need to hire more people to run your supply chain; you’re needing to help those people make better decisions.”
Bakker says, “This shift into adding leverage and expertise, versus adding capacity or adding speed to capacity processes, is an important distinction for where companies see the future.” For any MSPs looking to best support their clients as they pursue AI initiatives, this is a critical mindset shift.
Hiring MSPs Vs. Using AI In-House
Of the 201 businesses surveyed, 65% of them rely on MSPs to support their Gen AI usage. The other 35% currently prefer in-house capabilities.
The main reasons businesses are choosing to partner with MSPs in this way are expertise acquisition, in-house capability limitations, speed and time efficiency, and cost considerations. Organizations that are choosing to go it alone are doing so due to their specialized in-house expertise, goals of building internal capabilities, cost and data privacy concerns, need for regulatory compliance, and desire for customization.
The most significant reason customers are choosing to partner with MSPs to support their AI usage is to close a skills gap. “The skills shortage remains challenging and is driving the need for external support from MSPs,” says Michael Dornan, principal analyst and co-author of the study. “Gen AI has moved quickly, but many enterprises already wish they had started earlier, logged successes or failures faster, and used external support more in that learning process.”
“More broadly, you can think of it addressing either a skills gap or capacity for cost gap,” says Bakker. Those who are not partnering with MSPs want to have that expertise in-house, while those that do “expect [MSPs] to have the capacity and skills now. It’s a trade-off between wanting to develop those skills and speed.”
This indicates that the biggest competitive advantages your MSP can have when it comes to Gen AI projects are speed and expertise. The faster you can get a client going on their AI initiatives, the more likely you are to win the sale. This isn’t the time to learn on the job.
The Revenue Opportunity For MSPs
In terms of how MSPs can best support clients who are looking to start using Gen AI, Bakker says, “Help them actually start. Get something in production.”
As the study found, clients are using MSPs for Gen AI projects because “they want speed to value,” Bakker says. “So, help clients get something in production, so they can start seeing value first. Limit design workshops and assessments and back-end data adjustments. [Focus on] getting something that works for somebody. Even if it’s an internal tool. Get to something that is on, that people can access, so that they can start experimenting. That [will help] that idea development continue.”
Beyond that, Bakker anticipates a need for MSPs to establish systems to manage and organize their clients’ data. LLMs need to leverage data in order to function. The recent increase in AI usage has “put organizations on notice that their data has to be in good shape to be able to use these tools—and it is not in good shape,” Bakker explains. Now, companies are turning to MSPs to fix their data. In fact, of those companies using MSPs to support their Gen AI projects, half are using MSPs for data management work.
The Long Fix
“There’s a ton of work there,” says Bakkar. “It’s going to be a long fix for MSPs.”
In short, “Enterprises are hoping for big productivity, efficiency, and cost improvement gains from Gen AI, but with enterprise spending averaging $2.6 million on each Gen AI use case, organizations will need more scaled projects to reach their goals,” Bakker says. “For the foreseeable future, we believe the growth of Gen AI and the associated talent shortage will continue to drive growth in MSP contract activity.”
So, if your MSP hasn’t already started supporting your clients’ Gen AI projects, now’s the time to start. To learn more about AI as a revenue stream, check out our recent article on AI as a service—and why you need to offer it.