Challenges of AI Adoption in Firms
When AI engineer Malcolm was employed at a data analysis company, executives aimed to use generative AI to categorise their customer database into various personas.
"Don't use AI," was his advice.
He argued that a traditional machine learning model would have been more suitable, delivering consistent and repeatable results at a lower cost.
"They still went ahead with Gen AI," says Malcolm (a pseudonym).
This decision resulted in a process that was less accurate and more expensive, but it allowed the organisation to claim it was embracing AI technology.
Malcolm's experience reflects a broader trend where more companies are adopting AI and requiring their staff to use it.
Corporate Pressure to Adopt AI Tools
In February, global consultancy Accenture reportedly informed employees that promotions to senior roles would require "regular adoption of AI tooling," and that it would monitor usage of its AI platform.
Similarly, in May, competitor KPMG announced it had created a dashboard to track whether its US employees meet a 75% usage target for its AI tools.
The company describes this as part of "a holistic effort… to help people move up the AI maturity curve."
Other organisations are implementing AI more broadly but still expect it to transform daily work routines.
Government AI Initiatives and Staff Concerns
Governments are also looking to leverage AI capabilities.
The UK government is relying on AI to help "rewire" the state and enhance efficiency across Whitehall.
However, research by the civil servant union FDA reveals that while civil servants are open to using AI to improve productivity, there is skepticism about management's ability to manage the transformation effectively.
Less than a third of civil servants had been consulted on AI rollout plans, indicating that "change is being done to workers, not with them," according to the union.
FDA general secretary Dave Penman said the rollout was "inconsistent across departments which limits the productivity gains."
Unclear AI Strategies at the Executive Level
Dan Boyles, CEO of consultancy Hello AI Collective, notes that organisations often rush to highlight AI adoption without clarity on their objectives or expected benefits.
"I was with an oil and gas company, and I sat with the C-suite, and I just went 'what's the reason for using AI?' And none of them could agree."
According to Boyles, the CEO mentioned the need to keep up with competitors, the head of sales wanted to increase revenue, and the marketing team aimed to reduce reliance on external contractors.
This lack of consensus at leadership levels can lead to AI investments failing to meet expectations.
"I think the wreckage is organisations not getting the ROI [return on investment] from it that they were expecting and not getting their people engaging with it," says a senior consultant at a large consulting firm who requested anonymity.
In his firm, all employees have access to two AI tools and can request specialised tools for specific tasks, such as coding.
"If their job demands it, some of our people will have access to four or five AI tools."
He emphasises the importance of considering the human element, noting generational and potentially gender differences in confidence with AI.
Before accessing any tool, employees must complete mandatory training covering AI ethics and risks like bias. This training also highlights that AI tools can be sycophantic and prone to hallucinations.
Impact of Organisational Culture on AI Success
The existing culture within an organisation can significantly influence the success of AI implementation, as AI tends to accelerate processes positively or negatively, explains Caroline Rawlinson, CEO of Culture Amp, a company that monitors employee experiences and feedback.
Culture Amp reports that while 90% of HR professionals expect to increase their use of generative AI, one-third say "no one currently owns AI strategy at their companies."
"If you're putting AI technology on top of a fragmented culture or a fear-based culture, it is not going to succeed," says Rawlinson.
"At best, it becomes a very slow roll out as people don't understand what they're being asked to achieve or the tools that they're being provided with. At worst, it ends up as quite a big, wasted effort."
Aligning AI Use with Clear Business Goals
In the oil and gas company Boyles assisted, the president eventually clarified the key objective:
"I want to increase my operating earnings because I want to sell [the company] in years."
With this clear motivation, Boyles' team could engage each department to review their processes and technology, identify bottlenecks, and determine where AI could provide effective support.
