C-suite urged to clarify AI productivity expectations and focus on skill building

The consensus around generative AI in the workplace is that it has the potential to greatly accelerate employees’ productivity.

In theory, generative AI is a tool that can take on the repetitive, labour-intensive and time-consuming aspects of many jobs, leaving humans to simply oversee, polish, and refine – or focus on other tasks that require uniquely human capabilities like innovation and insight.

But in practice, according to a study published last month by The Upwork Research Institute, the research arm of freelance platform Upwork, generative AI may be having the opposite effect. While 96% of C-suite leaders say they expect the use of AI tools to increase their company’s overall productivity levels, more than three quarters (77%) of employees using AI report that generative AI has decreased their productivity and added to their workload.

The findings shed light on the problems with treating generative AI as a productivity silver bullet – and what can be done to remedy this.

Employees are ill-equipped to take advantage of generative AI

A major contributor to workers’ difficulty in taking advantage of generative AI’s potential and streamlining their work processes may be a lack of direction and preparation. Close to half (47%) of employees who are using generative AI say that they have no idea how to achieve the gains in productivity expected by employers. Thirty-eight percent report feeling overwhelmed about having to use AI at work.

Among the 96% of C-suite executives who expect their workers to up productivity with AI tools, just 26% have AI training programmes in place, while only 13% report a well-implemented AI strategy.

Upwork’s survey indicates that leaders may also overestimate their employees’ comfort and aptitude with generative AI. Thirty-seven percent of C-level leaders at companies that have implemented AI report that their workforce is “highly” skilled and comfortable using it – while only 17% of employees report the same level of skill and comfort.

This goes some way towards explaining the lack of resourcing around generative AI: company leaders may believe that it is a tool that can easily be deployed ‘out of the box’ to achieve more output and efficiency gains, rather than one that requires training and resources to use to best effect.

Either way, there seems to be a perception gap between the level of skill and preparation that company leaders believe is needed to employ generative AI effectively and the level that employees themselves need in order to feel confident and equipped to make the most of this new technology.

Human oversight required

Few workplaces would implement generative AI without some kind of checks or oversight; hallucinations are an ever-present risk, and most agree that the best output comes from the combined efforts of generative AI and human workers applying their knowledge, expertise or creativity.

However, the need to verify or add to AI’s output increases the strain on human employees for whom generative AI is meant to be a time-saving tool. Two fifths (39%) of Upwork’s survey respondents said they are spending more time reviewing or moderating AI-generated content; 23% also say that they need to invest time into learning to use generative AI, while 21% report being asked to do more work overall. Forty percent of employees report feeling as though their company is asking them to do too much when it comes to AI.

Eighty-one percent of C-suite executives admit that they have increased the demands on employees in the past year: of these, 37% say that they are asking workers to use AI tools to increase their output. Other demands being placed on employees are for them to expand their skillsets (35%) and work more quickly or efficiently (26%).

Speaking the language of skills: How to bridge the productivity gap

One remedy that Upwork suggests to tackle this problem is to improve the way that companies measure productivity: shifting the emphasis from speed and efficiency towards measures like contributions to strategy, creativity, and innovation. As the author of Upwork’s report writes,

“AI, and frankly people, can deliver success measures that go beyond quantity and speed. … By aligning co-created outcomes to AI programs, leaders can clarify the AI productivity expectations and goals of the business, better balancing the needs of both the business and workforce.”

The report author also urges organisations to “Build fluency in the language of skills”, focusing their talent strategy on identifying and building on the skills that they have within their company rather than focusing on job roles.

This can be easier said than done: while C-suite leaders feel clear on the skills that they need, most highly valuing skills like product management (48%), data analytics (46%) and generative AI content generation and modelling (40%), they struggle to understand the skills present within their business. Upwork’s survey found that just 40% of leaders say they have a high-level awareness of the AI skills within their organisation.

In a previous piece of research surrounding the changes in skills demanded by the age of AI, authors Kelly Monahan and Ted Liu commented on the need for organisations to approach skills differently. “Our latest research on generative AI reflects a skills-biased technology change happening … It is part of the reason why we foresee a theme of job transformation this year, as our research has found AI is unlikely to replace most jobs, but will certainly change the tasks and skills required for the workforce to generate value.

“As technology continues to progress, it remains critical for business leaders to recognize the emerging skills required to maintain competitive advantage.”