Reality Check: Real-World Thoughts on AI Buzz for MSPs

As AI buzz takes over the indirect channel, managed service providers need guidance. After all, there’s so much hype surrounding the technology, which has actually been around for a long time, that it can be difficult to sift noise from reality.

That’s what the session, “(Almost) Everything You Need to Know About AI: Tips and Best Practices for Building AI Solutions Customers Actually Need,” aims to help MSPs discern. On Nov. 1, at 11:05 a.m. ET, join five AI-and-channel experts for insight into how to take the AI buzz and use it to your advantage.

David Tan, CTO of CrushBank Technologies, will serve as moderator. The following specialists will sit on the panel:

Before that event takes place, however, we asked each panelist to provide some insight to help MSPs prepare. We heard back from Tan, Chouffani and Doebel; here, they contribute some thoughts to help you prep for the full session, and offer guidance for how navigating all the AI buzz. See below for the lightly edited Q&A.

Channel Futures: As the AI buzz consumes cloud computing conversations, what key insight can you extend to MSPs in advance of this session? What would you like them to come to the session already mulling?

CrushBank’s David Tan

David Tan: MSPs need to be thinking about who they want to partner with for AI solutions. That means for both internal solutions and solutions you build for customers. People think AI started the day ChatGPT was released, but there are great companies that have been building innovative solutions for years. Seek them out and understand what they are doing. I think it’s also important to realize there are differences in solutions that sound similar. I wouldn’t call this the “Wild West” but we are very much at the infancy stages. MSPs need to build the internal expertise to understand concepts like AI governance, model transparency, and all the rules and regulations that are coming down the pike. It’s an incredibly exciting space, but can be very dangerous if not navigated the right way.

Reda Chouffani: MSPs must be prepared to discuss some of the capabilities that businesses can leverage when it comes to AI, services and applications that can help further businesses.  MSPs should also consider how they can use AI within their own practices to support key insights from tickets, customer interactions and even lead generation.

Paola Doebel: We need to be thinking about AI readiness. Large enterprises are challenged with making meaningful use of their vast amounts of data. They recognize that establishing a robust data platform is a fundamental prerequisite to unlocking the full potential of AI. As MSPs, we have a unique opportunity to partner with our clients and facilitate this transformative journey for our clients, positioning ourselves as trusted allies in their AI endeavors. MSPs need to be focused on …

… not just the ability to deliver AI solutions to their clients (if that is part of their portfolio), but on leveraging AI for internal efficiency and quality of service.

CF: Generative AI sure seems to be the most popular form of AI right now. How should MSPs use gen AI to help customers improve their operations … or, to stir things up, is there a different type of AI MSPs might do better to employ for their clients’ benefit?

David Tan: Generative AI is hot, there’s no doubt. MSPs should talk to clients about how they can use it to assist people with the right expertise do their jobs more efficiently. In other words, things like letting your marketing team use it to build a marketing plan faster; helping a salesperson build a proposal; maybe let HR update and manage policies — again, things where the expert can chaperone the technology. Don’t let your clients think it’s a replacement for a person or job function. If you want to think about other areas or AI that clients can leverage, I’d look at things like semantic search or text analytics. There are a lot of very powerful platforms and solutions out there that can greatly benefit many different companies.

Biz Technology Solutions’ Reda Chouffani

Reda Chouffani: There are a number of AI services available today that MSPs can leverage for themselves and provide for their customers, from ChatGPT and content generation to image processing and data extraction models that can provide key capabilities to serve their clients.

Paola Doebel: While generative AI is the most popular form of AI, MSPs should approach AI selection with a focus on their clients’ unique needs. Rather than following trends, MSPs should evaluate which AI technologies … align best with their clients’ business goals. It’s essential to have a deep understanding of the specific challenges each client faces and tailor AI solutions accordingly to drive operational improvements effectively.

CF: Without giving away the meat of the panel, what one or two strategies should MSPs be thinking about – and implementing – right now when it comes to creating the right AI-centric teams and adjusting leadership roles to accommodate the AI onslaught?

David Tan: This is the age-old challenge for MSPs. New technologies emerge and they need to find the right people to evaluate, manage and implement it. AI is a little unique as there is a whole new set of skills required. Think about starting to hire or up-skill data scientists if you really want to be serious about building your own solutions. Otherwise, look for people with data competencies — think advanced business analysts.

Reda Chouffani: An AI task force to evaluate and implement AI would be one of the first priorities an MSP should be thinking about as customers and their competitors are considering, and looking actively for, AI to help support their business objectives and goals.

Ensono’s Paola Doebel

Paola Doebel: Implement ongoing training and upskilling programs for current teams to ensure they are well-versed in AI concepts and can proficiently use AI tools. Adapt leadership roles to incorporate individuals who possess a deep understanding of both the technical and strategic facets of AI. … When a transformative new technology comes along, it’s down to leadership to foster an environment that is inspired to leverage it. This can take the form of funding projects, assembling teams, and “making room” in employee’s goals and schedules to enable innovation to happen. Hope is not a strategy. An environment must be created to cultivate and support initiatives.

CF: What are one or two ethical considerations MSPs need to keep in mind re: deploying AI to help end users?

David Tan: It’s imperative that MSPs understand the …

… pitfalls they need to navigate with AI. Bias, hallucination, copyright implications, regulatory compliance, the list goes on. Before doing anything with AI, MSPs need to dig in and really understand what this means and how it can all go wrong.

Reda Chouffani: Data privacy and general bias in AI. While there are no real policies in place when it comes to how AI can be used and restrictions on some of the training sources for AI, MSPs must educate themselves and customers of the risks associated with AI.

Paola Doebel: The emphasis should be on transparency and responsible AI usage. MSPs must be cautious about biases in AI algorithms and prioritize data privacy. Ensuring that AI benefits, rather than harms, end users should be a guiding ethical principle.

CF: What’s one of the biggest AI-MSP challenges you hope to discuss during the panel?

David Tan: Understanding the difference between bolting AI onto a legacy solution … and really understanding AI and building it into solutions responsibly.

Reda Chouffani: How AI will change the support landscape and how MSPs serve their clients.

Paola Doebel: A significant challenge in the AI-MSP space is managing the delicate balance between automation and human touch in service delivery. We need to be thinking about strategies to effectively integrate AI without compromising the personal and ethical dimensions of our services.

CF: What one best practice helps to resolve that challenge?

David Tan: Build a robust checklist to evaluate solutions based on a trustworthy AI approach.

Reda Chouffani: Appropriate planning and in-depth evaluation of its implications.

Paola Doebel: Implement a gradual AI adoption approach, starting with routine, low-impact tasks and progressively expanding AI’s role as it matures. This approach allows MSPs to fine-tune AI systems and maintain quality service delivery.

CF: What one or two qualities/characteristics should MSPs look for in an AI partner?

David Tan: Transparency about what they are doing and how they are doing it. Willingness to protect their partners in case something goes sideways.

Reda Chouffani: Experience in the MSP space, and the ability to train AI with their unique requirements.

Paola Doebel: MSPs should look for organizations with a proven track record of ethical AI development and a commitment to data security and compliance. Look for case studies with impactful and measurable deliverables.

CF: What else about AI and MSPs would you like to share in advance of next month’s panel?

Reda Chouffani: AI is changing the way companies operate, from how their employees work to the way they interact with their customers. While most MSPs are still trying to get familiar with what AI services can be applied internally in their organizations to what their clients can leverage, it is important to be actively evaluating and researching the different capabilities of AI to maintain their competitiveness and ensure they stay relevant to their customers.

Paola Doebel: AI should be viewed as an enabler rather than a disruptor. MSPs should focus on how AI can enhance their ability to deliver superior service quality while keeping ethical considerations at the forefront.