stepped into the role of data readiness advisor, showed the Telarus findings. More than four in 10 (44 percent) said they rarely or never discuss data readiness with clients. An additional one quarter of respondents admitted data readiness comes up only occasionally during AI discussions. Telarus executives recommend advisors walk their customers and prospects through these “building blocks of data readiness.” • Data hygiene – Is your data clean, current and error-free? • Data accessibility – Can the right users and systems securely access it? • Data quality – Is it consistent, accurate and complete? • Context – Is it labeled and structured so AI models can interpret it? From here, a conversation can move to some key general topics surrounding existing infrastructure, skills gaps and eventual implementations goals, suggested Koby Phillips, vice president of cloud strategy at Telarus. For infrastructure and architecture, begin by mapping out the customer’s existing compute, storage and networking capabilities, as well as their cloud and edge deployments, to help assess whether current systems support AI readiness, said Phillips. Are AI workloads running on dedicated AI infrastructure? What types of storage solutions is the company using, and what connections are in place? The IT skills gap, meanwhile, is expected to impact as many as 90 percent of global organization by 2026, according to IDC, so for customers looking to implement AI, “it’s worth asking if they are comfortable with their current teams, or if they may need advanced guidance and manpower,” advised Phillips. Question here can center around how taxing AI implementations will be on IT teams and whether they will cause delays in other projects. With the emergence of agentic AI and the constant flow of new productivity tools, most companies will be looking to build upon AI pilots and initial deployments in order to take advantage of emerging capabilities. In turn, technology advisors would be wise to discuss near-term and longerterm AI investment priorities and how data readiness can help customers achieve those goals. Questions here can start with the more immediate concerns around how many streams of data are coming in, where they are landing and how they are connected, and turn to bigger picture discussions around the core business challenges hopefully being solved with AI and how the company sees AI being used a year to two down the road. Make no mistake, AI is no longer confined to the domains of pilots, innovation labs and exploratory meetings. It’s being rapidly deployed across most departments and is having a major influence on the spending in cybersecurity, cloud and CX, among other areas, the Telarus data showed. Solution distributors such as Telarus, vendors, publishers and research firms all are rushing to market with whitepapers, e-guides and training tools to help technology advisors build AI fluency. But until those materials can be absorbed and processed, it’s possible that channel partners will be compelled to start AI conversations with their customers and simply trust that their vendor and distributor partners will help close the deal and deliver the goods. It may not be an ideal scenario, but it’s much better than your customers having AI conversations with a competitor. o How often do you discuss data readiness with your customer when selling AI solutions? Never – It has not been a focus in my sales conversation 18% Rarely – Most customers don’t ask about it 26% Occasionally – It comes up in some AI discussions 26% Regularly – It’s a key part of every AI-related conversation 29% Source: Telarus Percentage of Attack Detections That Were Malware-free Source: ConnectWise Productivity Improved operational efficiency Improved customer experience Automation Innovation Modernization Cost reduction Improved employee experience Scalability Head count reduction If you are planning to adopt AI, what are the desired outcomes you are seeking? (Select all that apply) Source: Telarus Mid-market Enterprise 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 65%64% 60% 67% 52%52% 51% 78% 51% 28% 47% 30% 43% 64% 41% 25% 37% 25% 50% 16% 40% 2019 2020 2021 2022 2023 2024 51% 62% 71% 75% 79% 16 CHANNELVISION | JULY - AUGUST 2025
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