When you picture an innovative company, the image that likely comes to mind is a start-up with a small team working out of a garage, not a large, bureaucratic corporation. This poses a challenge for MSP roll-ups, which face increasing pressure from customers, employees, and investors to execute a compelling AI strategy.
Most MSP roll-ups have a centralized operating model within a national brand; decision-making authority concentrated at the corporate level and a one-size-fits-all tech stack. These features that roll-ups work so hard to build often leave them looking more like that large corporate bureaucracy than the nimble start-up.
Decentralized acquirers, by contrast, keep their acquired companies empowered and independent with a separate brand, an empowered local team, and a true CEO running each company. The result is that their companies remain agile and can evolve rapidly.
In this critical AI moment, decentralized MSP acquirers that keep their companies independent and nimble will outrun their centralized competitors in AI innovation.
The AI opportunity and threat for MSPs
The small businesses that MSPs serve are adopting AI much faster than they adopted cloud hosting, SaaS, and cybersecurity. In a recent survey, 68% of U.S. small businesses said they now use AI regularly. That’s up from 48% just a year earlier, and over a quarter are using it daily to streamline work.
For MSPs that lean into innovation, AI is an unprecedented opportunity to expand their value proposition, generate new revenue streams, and scale service delivery. 68% of SMBs use AI, but only a fraction of their employees use it securely with sensitive company information. MSPs need to educate and equip their customers with secure AI solutions.
As trusted technology partners, MSPs can leverage AI to automate workflows for their SMB clients. This transformative work will expand the MSP value proposition, but it will require both customer intimacy and empowering AI-forward team members to solve these issues.
Every MSP can improve the efficiency and quality of its service delivery through automation, but many are not capitalizing on the opportunity. Small MSPs often cannot dedicate time and resources to automation. National centralized MSPs have the resources to automate but lack the customer and employee intimacy needed to drive automation without degrading the customer experience. Decentralized acquirers are well-positioned to preserve customer and employee intimacy while investing in automation.
For MSPs that stand still, AI is a disruptive threat. MSPs that don’t serve as the AI river guide to their clients should expect their customers to look elsewhere for advice on AI cybersecurity, integration, training, and business transformation. MSPs that do not invest in service delivery automation will operate at inferior margins and will not be able to reinvest to expand their service offerings for customers. AI is coming for MSPs and their customers much faster than cloud or cybersecurity; it’s not the time to stand by idly.
Innovation in centralized and decentralized companiesCentralized models put decision-making in the hands of corporate leaders who are furthest from the customer, while the teams closest to daily operations and the customer are tasked with executing the top-down mandate. Innovation generally happens through corporate centers of excellence.
There is usually one strategy, one key AI leader, and a single project with a big budget and a long timeline to build some sort of an “AI Brain”. Customers, leaders, and employees will be interviewed about the type of AI innovation they’re looking for. 12 months later, they will be forced to adopt an AI solution that is unresponsive to their requests and does not fit their service delivery model or end market.
A decentralized model works differently. Local leaders are accountable for their own P&L and operate with a high degree of autonomy. In a decentralized business with an innovation-forward mindset, there might be dozens or even more than 100 companies innovating with AI. When successful innovations are identified, the holding company’s role is to facilitate their rapid spread across the group of companies. When experiments fail, the stakes are low because they are contained within a single operating company and do not spill over to the entire organization.
At Evergreen, for example, we have leveraged our decentralized structure to launch an entirely new AI-native operating company, transform three existing companies into AI Labs to test the limits of automation within MSPs, and scale AI resale and automation initiatives across dozens of companies.
Some of our best AI innovations have arisen organically from customer insights. At multiple companies, we have identified and executed on opportunities to automate manual processes (e.g., billing, quoting, AP) for our clients, leveraging AI. In our decentralized structure, these opportunities move from idea to action quickly because the operating company CEO is very close to their customer base and does not need corporate approval to pursue initiatives that better serve their customers.
In several cases, a single automation project has saved the company’s customers more money than they spend on managed services combined. Because automation services are not traditionally part of a managed services offering, these projects expand the company’s value proposition and generate new upfront and recurring revenue streams.
Trust and innovation
The fundamental difference between centralized and decentralized businesses is trust. In a decentralized business, leaders operate with autonomy because they are trusted to do the right thing for their customers, employees, and shareholders alike. That trust is, of course, earned and must be maintained, but it is never taken away by design. Centralized companies have trust in senior leadership, but the trust ends there by design.
This is a critical distinction in AI transformation because innovation is a power-law game, like betting on new business ventures. Venture capitalists would never put their entire portfolio into a single seed-stage start-up, but that’s effectively what centralized companies do when they put all their investment behind a single AI center of excellence.
If you were designing the MSP of the future and I gave you the following two options, which would you choose? The first option is to invest in a single, well-funded company, assuming they will get their AI strategy right on the first try. The other option is to invest in more than 100 empowered companies, all vying to design the MSP of the future, and then select a compilation of the best strategies that originate from that group.
I would choose, and have chosen, the latter option.
Scaling “bright spots”
But what do you do when one of your 100 companies pioneers a help desk automation strategy or a new AI revenue offering? How do you scale the impact of these breakthroughs?
We call these breakthroughs “bright spots,” and this is where the holding company’s role in a decentralized company comes into play. Our job is to identify bright spots, study them, and spread them across our operating companies. We never mandate that our companies adopt bright spots, but our incentives are structured such that any opportunity to better serve the customer, generate revenue, and expand our value proposition gets rapidly “pulled” through the organization, not “pushed” down from corporate. Some breakthroughs will be applicable to 100% of our companies, others might not be one-size-fits-all, and that’s okay.
Choose your acquirer carefully
Acquisitive MSPs today are still finding their footing on AI, but the real question is, will their structure support innovation? This is crucial, especially if you are thinking about selling your business to an MSP acquirer. Does your buyer allow acquired companies to try new things? Will they let your customers and employees inform your AI strategy? Are they AI forward or are they dismissive of AI? Do they have tangible examples of generating revenue or increasing margins leveraging AI?
The MSPs that emphasize trust, innovation, and agility will lead the way on AI innovation. Joining a decentralized platform offers access to additional resources and dozens of peer companies to learn from, without stripping away the autonomy that got your business to where it is today.