The level of attention on generative AI (gen AI) in business is no longer a surprise. It promises game-changing disruption – faster and more cost-effective operations, improved customer and employee experiences, and a competitive edge. The fact is that gen AI is evolving at such a rapid pace, it’s hard to know when to jump on the bandwagon.
Tech and industry leaders are still working out how gen AI will change the world of work. There are big and important questions to address. What are the practical use cases for the appropriate risk profile? What needs to be in place to enable the right data landscape? Understanding the landscape is crucial for any enterprise to stay competitive today, but the urgency increases significantly when preparing for the AI world of tomorrow.
A recent survey by 451 Research of 650 business and IT leaders sheds much-needed light on the adoption of gen AI and its potential benefits, particularly in automation and integration within businesses.
The eternal quest for efficiency
IT teams were created so that businesses could ‘do more with less’. Over the years, many technology advancements, including low-code integration and automation, have delivered on this promise.
Take an employee onboarding task for example. Traditionally involving manual coordination across numerous departments, the end-to-end process can be streamlined through automation and integration, seamlessly transferring employee information, providing equipment, assigning training, and setting up payroll and benefits, all in one automated process. It is slicker, quicker, and cheaper than doing each action manually.
There are also huge benefits to having back-end data sources connected and synchronised. Data synchronisation, governance, security and quality control are critical to ensuring modern data pipelines are trusted and up-to-date. Managing all this from a central location while not relying on point-to-point solutions is the key to success.
Modern businesses generate and collect vast amounts of data from various sources; a typical employee uses upwards of 40 business applications and software tools every day. This growing complexity, especially in managing data across modern IT setups, means many struggle to stay on top.
The scale keeps growing and the demand along with it, so we are still being asked to ‘do more with less’. Now we want to do-more-with-less at the same time as ‘working-smarter’ – and we no longer look just to IT to deliver on this; the business side is sharing the burden. Enter generative AI.
Gen AI for automation and integration
The 451 survey reveals gen AI is highly regarded when it comes to driving automation across processes and tasks, and it is already being put to work by most businesses. More than half of the leaders polled in the research said gen AI is either already deployed as a priority, or is in their strategic plans for automation.
The same goes for integration. In fact, just over two in five business and IT leaders are currently using some form of an AI-assisted integration platform, and over half say it is a high priority for integrating data, apps and processes.
Such high enthusiasm and uptake is because leaders genuinely see gen AI as a game-changer. It will bring benefits like improved automation accuracy and cost reduction, and foster innovation and streamline operations, as well as help to optimise resources. Gen AI is also seen as a solution to simplify integration of various types, with nearly all 650 respondents to the 451 poll agreeing that virtually all integration types can benefit from gen AI-assisted platforms.
There are, however, challenges to be aware of too. There are several key issues reflected in the survey that you need to address before powering on with any gen AI initiatives. The survey flagged security and privacy as top concerns, closely followed by data quality and availability. There is also anxiety about the financial implications on gen AI deployments, integrating with current systems, and the scarcity of appropriately skilled individuals.
Other challenges include ensuring regulatory compliance, maintaining model training accuracy, overcoming resistance to change, establishing effective governance, and addressing algorithm bias. Each of these is unique and must be carefully considered relative to the business and use cases.
What business leaders need to do next
As leaders embrace gen AI for key business functions of automation and integration and beyond, there are some sensible and significant steps to take. This is by no means a comprehensive list but three top focuses should be on upskilling teams, setting clear strategies for gen AI implementation, and ensuring robust data management practices are in place.
This last one is ultimately the most important, because data is the lifeblood of gen AI. However powerful the AI is that you deploy, it is only as good as the data it is fed. Don’t expect complete, accurate, or comprehensive results if the data that goes in is incomplete, inaccurate, or otherwise not up to standard.
The work that needs to be done by businesses today to manage and maintain high-quality data will absolutely be essential to empower gen AI. Its ability to function effectively and deliver transformative benefits relies on it. Data quality, management, strategy and oversight should be top priorities from now on.
The survey results show that enterprises are already reaping the rewards of gen AI for automation and integration. Business and IT leaders need to kickstart their own gen AI programmes to keep up. But do so strategically, and above all, manage your data well. Otherwise, the quality of what you put in is what you get out, and no amount of artificial intelligence will make it better.
