The extraordinary capabilities of generative AI (genAI) platforms have captured the business world’s imagination – and a growing portion of its IT budgets. Yet even as tech giants work to make genAI technology more accessible, experts warn that companies focused solely on that technology are bound to fail.
That’s because genAI isn’t a silver bullet for every business problem, and simply directing developers and IT leaders to join the stampede towards the technology is unlikely to deliver the benefits that business leaders actually want from the technology.
“Organisations have a wide variety of reasons” for embracing AI, noted James Finley, senior systems trainer with training provider Lumify Work (formerly DDLS in Australia and Auldhouse in New Zealand). Lumify offers a range of AI intensive training courses, including its 8-week CloudUp and AWS Generative AI Accelerator boot camps, AWS Skill Builder on-demand digital training, and AI-related practitioner certifications.
In working with early adopters across the ANZ region, Finley has seen companies embracing AI for both internally focused projects – those using the technology to improve internal efficiencies – and those building “externally facing solutions” to support customer care and other operations.
“Every organisation is different, and it comes down to what their first jumping-off point is,” Finley said, “but I am seeing people coming from a wide variety of platforms.”
Perhaps instinctively, he noted, early adopters are often technical – data platform experts, infrastructure, sysops or developer team members – with many people doubling up on roles as enthusiastic team members expand their skills in more than one area.
Many companies “are looking at people they know and trust internally to get that foothold,” he explained, “but when they get some known quantities and start saying that they need more staff, they need someone who understands the business and what they’re trying to achieve.”
Extending AI from technical project to business driver
Jumping this gap from technical project to business driver is essential for AI success, and truly integrating AI into the business requires time, patience, and widespread buy-in.
Without such buy-in, many executives risk becoming disillusioned by AI in the short term, Gartner recently advised while predicting that companies will abandon 30 per cent of genAI projects by the end of 2025.
This attrition will be writ large as organisations drop millions on integrating genAI services into their apps and building custom models from scratch, then find they solved a different problem than they needed to – or committed resources to solve business problems without considering whether AI was even the appropriate solution.
The benefits of genAI “are very company, use case, role and workforce specific,” Gartner distinguished VP analyst Rita Sallam said, noting that the impact of genAI projects “may not be immediately evident and may materialise over time.”
Indeed, some estimates suggest that 80 per cent of projects will fail – twice the rate of non-AI projects – with one recent study blaming a range of issues, including stakeholders failing to effectively communicate the problem that needs solving; lack of the necessary data and infrastructure to train and deliver AI; or teams focused more on the latest and greatest technology than on solving real problems for their users.
Keeping that focus can be tough given the sheer breadth and capability of genAI and broader AI capabilities available through APIs that tap services like AWS Bedrock, which offers developers a smorgasbord of technological solutions encompassing a range of genAI technologies.
“The foundation models are capable of doing a whole bunch of things,” said AWS technical trainer Peter Vandaele, “and then it’s up to you as a programmer or as a developer to focus it so you can integrate that into your own application.”
“We try to be very, very broad and allow you to use that inside your application through a simple, unified API that lets you start adding more things like extra knowledge bases or even giving it agency to execute tasks.”
“It’s not doing your job, but it is an assistant.”
Where are the champions?
Many technical staff will have dabbled in AI for their own knowledge – either by experimenting with hosted AI systems, or by working on early-stage pilot programs – but companies looking to get serious about AI must consider a more structured program of technical and business training to ensure the whole company is on board.
“Understanding how to unlock the technology through core cloud training and skills is absolutely critical to be able to make the most of AI,” explained Leif Pedersen, APAC cloud and AI product manager with Lumify Work.
Once known as Dimension Data Learning Services (DDLS), Lumify has positioned its broad range of technical and business training offerings as what Pedersen called a “one-stop shop for organisations and customers to come get everything they need from a training and development certification point of view.”
Yet such training is only part of the change that companies need to plan in order to make their AI and genAI projects a success: companies also need to cater to non-technical teams by establishing internal teams to advocate and train employees in ways that are meaningful to them.
As in many other business change projects, the appointment of ‘champions of change’ can be invaluable to helping extend AI culture across the organisation.
“Any sort of adoption process or cultural change inside an organisation, really just needs some champions to pick it up,” Pedersen said, noting that companies choosing technical AI training should also consider how to identify and train those champions.
Ultimately, technical teams and AI-focused managers should engage with those champions to build end-user acceptance of new technologies that will improve the way they work.
“This is not something that should be forced down from the top,” said Vandaele. “You want buy-in from the ground up, and training can really help blanket the organisation with education.”
This is particularly important regarding genAI, he added, because “there’s a lot of talk about it, a lot of buzz, and a lot of myths and fear going around.”
“The more we know about something and the more we understand something, the less we fear it – so it is going to be really important moving forward that organisations spend time really creating buy-in on a very broad level.”
Click HERE to learn more.