87% of C-Suite executives feel under pressure to implement GenAI solutions at speed and scale, according to RWS.
Despite these pressures, 76% expressed an overwhelming excitement across their organization for the potential benefits of GenAI.
However, this excitement is tempered by 36% of executives who raised concerns that there is an extreme danger of enterprise resources – which could be better deployed elsewhere – being diverted toward GenAI. 65% of executives see a real risk of an AI backlash in the coming years due to the current hype.
In keeping with this either-or dynamic is how AI is persistently presented as a threat to human employment. Countless headlines zoom in on the prospect of job substitution. This stokes fear, uncertainty and doubt among employees – even as business leaders profess their excitement about the technology’s transformative potential.
Fears aren’t limited to employees, however, with our executive survey respondents making it clear that they’re genuinely concerned about being left behind in the race to implement GenAI.
“Recent advances in GenAI have triggered an innovation race,” said Mark Lawyer, GM of Linguistic AI at RWS. “In a bid to be first past the post, there’s a real risk of failing to see any value from AI investments. It’s critical that business leaders are not reactive or piecemeal, but rigorous and purposeful in their approach.”
Enterprises embrace advanced automation and AI
While 43% of executives believe that GenAI is critical to retaining their competitive advantage, 68% acknowledge that they find it difficult to identify genuine innovators in today’s noisy AI market. Consequently, 60% of executives prefer to collaborate with trusted partners, and 43% favour innovators who combine technology, AI and human expertise.
“Enterprises are seeking advanced automation and AI from global content partners, prioritizing trust and security. Providers that combine the latest generative AI with human expertise will give their clients a distinct competitive advantage in the race to global market share,” comments Dr. Arle Lommel, senior analyst at CSA Research.
The survey shows that 20% of respondent organizations (rising to 27% in the USA) prefer to build GenAI solutions in-house, compared to 60% who prefer collaborating with trusted partners.
An important part of this journey for many organizations will be to step back from the pursuit of in-house development, with all the expertise and resources this requires. Instead, they’ll learn to work with trusted partners who understand the technology, enterprise requirements, and the importance of process integration and who live up to the demands of robust security.
Biggest risks around GenAI implementation
Responsible organizations actively exploring GenAI solutions demand to see objective security certification (such as ISO 27001).
Interestingly legal and compliance issues are not top priorities – perhaps because the perceived need for AI adoption ’now’ trumps legal and compliance considerations and/or focus, which may also not be totally clear.
The next biggest risks in the abstract and active exploration of GenAI solutions are the accuracy and reliability of model outputs. These are well-documented issues with LLMs – including their propensity to ‘hallucinate’.
In the abstract, skills and costs make up the top five risks. In active exploration, however, we see data privacy and confidentiality, documented ethical impact assessments and the impact on CX rising to the top.
Organizations should take a cautious approach toward GenAI
GenAI is here to stay. The sheer weight of investment and the vast volume of experimentation currently underway guarantee that it’s not going away any time soon.
Organizations today can’t afford to turn their back on the technology. The weight of expectation is too great, not least from employees, with 75% already using AI at work and happy to use their own solutions if their employers aren’t moving quickly enough.
Banning GenAI in the workplace can rapidly lead to an explosion of this shadow usage. This brings serious risks, including the sharing of sensitive, confidential and personally identifiable information. It’s far better to engage and educate employees and have a usage policy in place.
Innovation is hard work. It demands systematic, structured efforts to identify use cases and develop applications. With GenAI and LLMs especially, organizations should take a cautious and responsible approach – or risk a backlash from stakeholders.