As AI moves beyond experimentation to deployment, those in the boardroom are already realising the benefits it brings in terms of innovation, automation and more advanced workloads, says Ashley Gatehouse
Much has been made of the arrival of Artificial Intelligence (AI) within the enterprise. In recent months the subject has been much debated everywhere from boardrooms to the World Economic Forum (WEF).
As the British Prime Minister, Thersea May, told those recently gathered in Davos, “We are only at the beginning of what AI could achieve,” explaining that in the UK new AI startups were being created every week.
May went further though, suggesting the echoing of moves from within the enterprise, as she said she was prepared to “bring AI into government” as part of a wider strategy to ensure the UK was seen as a leader in this area – one reason she intended to press on with plans for the world’s first national advisory body for AI, committing £9m to the cause as it also announced that the UK will join the WEF council on AI.
As we know, many enterprises are already moving well beyond the experimentation phase to deployment, with recent research from Infosys confirming that AI deployments have already altered the way they operate. Indeed, having asked the question of more than 1,000 CXOs with decision-making power around AI, 90 percent said it had already had an impact on their organisation, with almost three quarters of those questioned stating it had transformed the way they went about their business.
These changes in such a short space of time also suggest that those firms not making provisions or plans for AI within their enterprise strategy would be making a grave mistake. With 80 percent of respondents recognising that AI would have some part to play in shaping their future strategy they indicated that they would almost certainly have to follow suit or be left behind.
And whereas once there was caution and scepticism when AI was mentioned – particularly around jobs and how they would be affected – there has been a general shift in mentality on the subject with enterprises making moves to harness such technologies to work in parallel with human masters to achieve things not possible just a few years back.
Consider the impact artificial intelligence and automation brings to various industries; the barriers it breaks down. Rather than replace, it fosters many new ways of working, bringing in other disciplines and human skillsets to help manage the process. In that respect the innovation and automation it is rapidly ushering into areas such as product design, engineering, predictive modelling and decision making itself, means it will certainly help to create jobs in other areas such as compliance.
Let’s not forget the innovation AI can bring when it comes to optimising insights and things like consumer experience. According to Infosys 80 percent of IT decision makers at organisations in later stages of AI deployment reported that they are using AI to augment existing solutions, or build new business-critical solutions and services to do this. By forcing us to think in new ways AI is helping firms to make rapid gains in both productivity and efficiency when deployed within the enterprise.
At the heart of this data remains the most precious of assets, but in some cases, for the moment, an obstacle. While the technology has moved swiftly on to allow enterprises to use it in a multitude of new ways, almost half of IT decision makers have reported that they’re not quite there in terms of being able to support the new technologies and this is forcing them to invest in data management as they bid to harness the benefits it will bring.
However, once there, AI will help to lessen the load for CIOs and IT directors and open up business intelligence (BI) and data analytics to a whole new stream of non-data professionals within firms. In turn that will allow for new insights when it comes to BI, whilst reducing the reliance on custom build solutions as AI reduces the barriers between data formats opening it up for analysis and application alongside machine learning for new and profitable areas such as data discovery, cleansing and curation.
Of course, the next generation of cloud tools are already here for enterprises to start developing new strategies and methods of IT delivery. Witness the application of Microsoft’s Azure ecosystem and how this is helping firms to handle more advanced workloads, such as big data analytics and AI-enabled applications.
Indeed, today’s intelligent cloud and edge solutions allow organisations to harness enterprise-grade AI infrastructure running AI workloads anywhere at scale, something few would have imagined just a few years ago. And that can only be a good thing for those within the enterprise.