As the world becomes ever more data-driven, the complexities of managing, assessing and actioning insights from the vast swathes of information now flowing into businesses by the second becomes increasingly complex. Against this data flood, the introduction of generative AI technologies, which can filter the onslaught, automate the process, and analyse even complex and disparate datasets in a matter of moments, is a welcome development. And yet, the world remains cautious as to how this evolution from machine learning automation to smarter, more responsive generative solutions can assist in enterprise use cases, without supplanting the need for workforces, and ensuring that human assessment remains baked into the response decisioning process.
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As the development of generative AI is so rapid, we wanted to better understand on a global level how enterprise businesses are integrating this technology. We conducted a survey of those responsible for data and technology within organisations across Latin America, Spain and the UK, and set to benchmark how these experts are approaching the raw potential, rapid integration and educational challenges within their businesses to seize the opportunity generative AI presents.
First and foremost, what came through loud and clear was the enthusiasm and excitement for this technology from our expert audiences. Nearly all (99%) of our respondents, across all three regions, told us that those not integrating generative technologies were actively ‘missing out’. This full-throated enthusiasm for the potential for generative AI to help businesses to interpret data more accurately, and at scale, continued in other areas of our findings – 92% of those using generative AI in their roles were fully satisfied with the results, and three-quarters are excited about the future potential of the technology for their roles.
Furthermore, rather than expressing fear about how their jobs might be impacted by generative AI in the months and years to come, a third anticipate that their roles will be much more integrated with generative technologies within the next 12 months.
While this audience were clearly enthused about how generative deployment can help their businesses to thrive, only just over a quarter (27%) of businesses had a strategy to harness this technology on an enterprise level. Those with their arms around enterprise data and IT challenges clearly see the opportunity to integrate further with this technology. However at an organisational level, understanding and education on how generative AI can drive business success proved to be lagging behind. Without this more evolved understanding of precisely what generative AI can, and currently cannot deliver, more general fears still persist beyond the boardroom table.
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For example, the survey reveals that trustworthiness and quality of responses to interrogation of company data are still questioned, not to mention the technology remains overshadowed by issues around potential security risks. Concerns were also raised at the sheer pace of generative AI’s development, and how businesses could reliably select a solution before a frontrunner technology emerges from the pack. This was reinforced by the discovery that 58% of businesses are struggling to keep up with the rate of evolution in the generative AI space. And yet, some 75% of our respondents are satisfied with the levels of training provided by their organisations on generative AI technologies. This suggests that the IT, data and tech departments within enterprise-level operations are those driving and implementing their generative AI development throughout the business infrastructure.
Even with this seeming lack of understanding from other departments, those with a good grasp on generative AI are forging ahead. Over half of respondents are harnessing its potential for speeding up processing and analysis tasks, and similar numbers grasp the opportunity for automating more routine processes. This suggests that the immediate need within businesses is for generative AI to become the workhorse, picking up bulk, low level, mass data tasks while the experienced human engines of data analysis focus on the greater-value analysis and strategy. These decision-makers also have a clear vision and ambition for how generative AI integration can help their roles to develop too, with just over one in five (21%) citing ambitions for greater automation to help to identify patterns in data, future trends and even consumer behaviours. Only slightly fewer (16%) have their sights set on AI helping to streamline and identify efficiencies across business structures too.
As an international benchmark, this research shows that not only do those responsible for generative AI introduction see a clear path for its initial adoption into data processing and analysis, they are also keen to be the custodians of the technology, proving its strategic worth to enterprises beyond the analysis and processing of complex information. There may currently be lingering concerns regarding accuracy and security for some. However, the development of the wider generative AI landscape and a greater integration of these technologies into enterprise infrastructures will dispel these myths, while simultaneously underlining how structured processing and analysis of data can unlock further opportunities and insights to drive business success. If this report highlights one particular truth regarding generative AI introduction into modern business, it is this: that early adoption and ownership among key IT decision-makers is proving that the technology has a bright future within modern, data-forward business structures.
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