Guest post by Francis O’Haire, Group Technology Director for Climb Channel Solutions Ireland
AI is on everyone’s minds these days, and for good reason.
IDC predicts that organisations will spend over $630 billion on AI by 2028. The potential of this technology is immense. But for the IT channel, the question is not just about what AI can do—it’s how to unlock its value. From infrastructure demands to security concerns, AI presents challenges that must be addressed strategically and there are key implications of AI for the channel which need to be navigated for organisations to seize the full potential of this emerging technology.
Infrastructure Demands
One of the first challenges AI poses is the sheer amount of infrastructure required to support it. We’ve all heard about public AI models—like ChatGPT—developed by large enterprises with massive data centres. But even as private AI models proliferate, organisations are grappling with the limitations of existing infrastructure. The fight for the hardware to support AI models, especially as businesses build their own, is intense. We’re seeing a massive lack of infrastructure to handle the computing, storage, and power demands that these models require.
Many channel partners have been, or soon will be, faced with the question: how do we help our customers scale up their AI initiatives when the available infrastructure simply isn’t enough? This is a problem, but it’s also an opportunity for partners to bring tailored solutions to help modernise data centres or offer cloud-based alternatives.
Data: The Fuel of AI Models
AI is only as powerful as the data that drives it. Clean, secure, and reliable data is the backbone of any AI model, but obtaining this kind of data isn’t easy. One of the most significant challenges is ensuring the cleanliness and security of data as it moves through various channels and across borders. Data governance is a vital part of this equation.
Data issues aren’t just a problem for AI developers; they’re a concern for every organisation leveraging AI. The question of data provenance—where it’s coming from, how it’s secured, and whether it’s being used ethically—presents a key challenge for channel partners, especially those involved in data security and compliance.
Security: Safeguarding AI Systems
Security is perhaps the most important consideration for AI use, especially given the vast amounts of data being fed into these models. The data used to train AI can be vulnerable to manipulation and threats such as prompt injections, adversarial attacks, and privacy violations.
Channel partners have an essential role to play in mitigating these risks. For example, as AI adoption grows, there will be a rise in demand for tools that can govern and secure AI systems effectively. We’re already seeing frameworks like ISO 42001, which provides standards for AI management systems, come into play. As governments implement legislation—including the EU AI Act—it’s critical for partners to guide customers in staying compliant, especially when managing AI adoption across international borders.
Skills: Bridging the Talent Gap
The talent gap in the AI and cybersecurity markets continues to widen. Due to the shortage of AI talent, from data scientists to engineers, businesses are struggling to secure the skills necessary to develop and manage AI models. The talent pool in the AI space is not only limited, but it’s also being quickly monopolised by large organisations. Many of the world’s top AI experts are being absorbed by service providers and big tech firms, leaving SMEs struggling to find the expertise needed for AI initiatives.
This talent crunch can be spun as an opportunity for channel partners, due to their ability to step in and provide these critical skills through managed services, consulting, or direct AI solutions. As with any service, customers engage with partners to access specialist skills – AI is no different. There will be heightened demand for trusted advisors who can support the modernisation of infrastructure and deliver the right services to support AI goals and initiatives.
Infrastructure: Building the AI Tech Stack
AI spans many different technologies and vendors, creating a vast and complex ecosystem. For channel partners, this presents an opportunity to help customers build a comprehensive AI tech stack, composed of reliable, secure, and proven tools. Developing expertise in key areas like software development, advanced data services, and AI-specific hardware will be crucial.
There’s no one-size-fits-all solution when it comes to AI, and that’s where channel partners can shine. It’s all about finding the right tools, testing them thoroughly, and delivering them in a way that makes sense for customers. The goal should be to simplify AI adoption by providing customers with a tailored stack of products and services that deliver results, while upholding compliance standards and supporting effective governance of this AI infrastructure.
Balance: Taking Responsibility to Capitalise on Opportunity
The Gen AI revolution alone represents a $158 billion opportunity for the channel by 2028 – but this is only the beginning. Channel partners who can adapt to the AI-driven landscape will be positioned to ride this wave of growth. The opportunities are vast, but so too are the responsibilities. It comes down to striking the right balance to enable innovation and governance, build infrastructure and security, and deliver specialised talent and comprehensive solutions.
Ultimately, wherever customers are on their AI journey – whether they’re adopting tools like Microsoft Copilot or building advanced AI-driven software stacks – the role of channel partners is to make AI adoption accessible and successful. In turn, customers can be empowered to thrive.
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