In our latest research, 82% of Channel leaders felt that AI would be impactful over the next 12 months. We hosted a Q&A with our Chief Operating Officer, Sara Wilkes and her among others have share their thoughts on the future of AI.

What is generative AI?

Traditional AI relies on rules and programming to perform specific tasks, like asking Alexa for the weather forecast, or Netflix recommending the next box set you should watch. Generative AI on the other hand is all about new original content. Most people are familiar with Chat GPT and its ability to generate new human-like outputs in a matter of seconds. But almost anything that can be represented digitally can be produced using Generative AI – music, video, images. From generating countless interior design options for your living room to composing your own unique soundtracks in seconds, the possibilities with Gen AI seem endless.

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Where will customers use the technology?

Most customers will be using generative AI to some extent already. A lot of software solutions have generative AI functionality built in, for example Microsoft’s co-pilot can summarise documents, write emails or minute meetings. For creative teams, Gen AI is writing copy and editing imagery. Others may be using AI to assist with analysing data and finding trends. In Agilitas’ 2024 Channel Trends research, 37% of channel businesses that we surveyed are already using AI chatbots with a further 33% looking to utilise this technology in the next 12 months.

What use cases need to emerge to generate further adoption?

Gen AI is a rapidly developing technology and there are still a lot of unknowns that exist. Generative AI analyses patterns from large data sets but the outputs are still inconsistent, can be biased or in some case wrong. I heard this great story of Chat GPT creating a research report full of statistics and when the user asked Chat GPT what the reference was, it responded with “I made it up”. Therefore, there is still a lot of human interaction required to ensure the output from Gen AI is accurate.

Another major concern affecting adoption rates surrounds security of sensitive data and company IP. Until organisations can be confident that their data is secure, I think we will see cautious rates of adoption. There is also the financial barrier to adopting Gen AI. Even if companies take advantage of open-source models, significant investment is required to ensure they are secure and trained correctly.

How can the channel make money from Gen AI?

For those channel companies that don’t leap into Gen AI, there is still the potential to make money by using AI to improve productivity levels, therefore being able to use resources to focus on other key revenue-generating areas. However, the risk-reward for those companies wanting to explore AI opportunities further could be far greater. AI Consulting services, developing custom AI solutions, providing AI integration services and offering AI training are all going to be areas in demand over the coming years.

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