Data, both the business and personal kind, is fast becoming an essential utility like transport, energy, and water. It is critical to the efficient functioning of modern life, and I honestly do not believe that we could do without it.
How we live, administer, manufacture, invest, plan, research, sell, buy, deliver, and even connect with each other have all changed beyond recognition thanks to data technology.
As Sir Nigel Shadbolt, chair of the Open Data Institute, says, data infrastructure is critically important to modern society, as it can help to create huge amounts of economic value.
And thanks to developments in data technology, as well as advanced algorithms and super-fast processing, we now have artificial intelligence (AI) that is capable of seeing and learning from patterns in data.
The promise of AI is that it will make businesses more efficient and effective, increase profits, reduce costs, and generally make life easier and better for us all.
However, despite AI’s potential to help us lead more informed lives with increased productivity and greater profitability, there are several barriers that are slowing adoption.
As the demand for AI solutions grows across all industries, we are faced with a talent shortage. Finding the right people, who have the combination of skills and knowledge necessary to unleash the full potential of AI is an increasing problem, and underpins the already growing “digital skills gap” in our society.
As a result, this growing industry has a relatively small pool of people with appropriate skills to choose from. It is natural to look for talent abroad, but this may not be the solution due to the continuing uncertainty around Brexit and its ever-shifting sands. And so the problem is likely to be exacerbated.
A further barrier to AI adoption is risk aversion – or fear of the unknown – at the c-suite level.
Those within an organisation who are inclined to champion AI will understandably reverse course if they don’t have executive backing.
This lack of support can often be attributed to poor understanding of how the technology works or the benefits it delivers. It can be difficult for a business leader to see the profit generating potential of an experimental AI project. Other business opportunities can easily take priority.
However, few problems are intractable, and these roadblocks can certainly be surmounted. For instance, data storage and processing capabilities can be bought through utility models that are highly scalable, very efficient, and allow businesses to innovate more easily.
By outsourcing these crucial IT infrastructure requirements, a business can not only reduce costs and avoid risks, but also bring in talent and expertise. The technical requirements and knowledge of how to implement AI requires not only the right technology, but the right people and processes too.
In addition to this, companies should invest in building an AI mindset by preparing employees with the necessary education, ownership, tools and processes that they require.
This will have tangible business benefits. According to a research survey of 1,075 businesses across 12 industries, the more that companies embraced employee involvement in AI design and deployment, the better these initiatives performed.
AI is inevitable and will bring its own winners and losers. Those that can master the power of this technology will enjoy competitive advantages that they could only dream of today.
I have no doubt that – when it comes to their infrastructure requirements at least – many companies will outsource their way to achieving success.