For many people in business, introducing AI into the enterprise can be a daunting task. Historically, it has often been difficult for CIOs and CTOs to gain the confidence of the boardroom and drive investment into AI so that Enterprise AI can be truly integrated into the fabric of the business.
Many companies who currently believe they are using AI are, in actual fact, not. While there are a number who are experimenting with AI, few are actually implementing at full scale across their business. Implementing Enterprise AI on such a small scale may be cheaper but it doesn’t make the full use of AI and so therefore the best value for money.
Further, as it can be difficult to show projected return on investment, many businesses find it difficult to get out of the starting gate when moving from using traditional, methods to fully integrated Enterprise AI. Therefore, most companies opt for a more traditional optimisation where they use advancements in computing and algorithms to optimise last mile logistics, routing, risk management activities and financial crime monitoring instead of exploring the full uses of AI.
Why should businesses be investing in AI?
Enterprise AI is historically difficult to land in enterprise
There are two main problems that have historically hindered the introduction of Enterprise AI; namely data curation and company culture.
Data curation is the management of data right through its life-cycle, from creation all to way to it being deleted. Historically, there has been a lack of data curation and labeling of data that could be used in the generation of training data for AI algorithms. Traditional businesses were set up to transact, not to curate data. However, this is proving to be a difficult message to swallow and as such is slowing mainstream adoption.
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Secondly, in many businesses, there has been a culture of looking at short-term results, with CEOs often under pressure to immediately generate profits and value for shareholders. Enterprise AI generally does not show a return on investment very quickly. As a programme of investment, undertaken over a number of years, it is not a quick fix for next income report.
This short-term thinking and subsequent search for a quick fix, rather than long term transformation, is preventing companies from viewing Enterprise AI as an investment and a long-term benefit. As such, no real investments are made in AI. Many businesses will generate a lot of hype around investing in AI but very few make a real investment beyond tooling and experimenting.
Changing the culture to bring down adoption barriers
For companies to successfully integrate Enterprise AI, there needs to be a couple of changes made internally. The first is the acceptance that during the integration stages there will be an aspect of trial and error. AI requires a culture where failure is tolerated so an improved bespoke service can be developed. This is often counter to the traditional IT culture in companies. With the average tenure of a CIO increasingly measured in months rather than years, it can be hard to invest in Enterprise AI and have continual drive to keep investing in the company.
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Further, many CEOs have also not received education around AI. It is common for businesses to have had issues with digital transformation in the past, having received little return from previous projects. As such, AI is often viewed as the latest fad and many leaders are reluctant to invest money in its development. However, Enterprise AI holds so much promise in terms of business transformation that organisations that embrace test and fail will learn quickly and be able to embrace the wave of disruption coming. It is important that CIOs communicate the value of investing in a long-term AI investment so as to continually implement and develop AI in the business.
Highlighting the business benefits of Enterprise AI?
There are a number of benefits to be gained from introducing AI, most notably that it will fundamentally improve the way business is done. Fully integrating AI into a company with a long-term mindset will improve efficiencies and secure critical data.
In the future, companies will find themselves in an AI arms race on who can mass training data, AI platforms and AI talent the fastest and most effectively. Acquiring the means of great AI to solve and optimise business transactions will ultimately decide the success of a company. Implementing this early on will ensure companies are ahead of the curve and are able to continually update systems rather than implement late in the game, wasting more time and money.
Business should be focusing on accepting AI as a long-term investment. The focus should be how to create an investment programme focused on AI in the longer term and change the organisational culture to really jump into AI and appreciate the future benefits. Paradoxically, the real innovation in Enterprise AI will come from making businesses ready to adopt AI, not in the actual training and implementation of AI which is becoming ever more commoditised.
Gary Richardson is MD of Emerging Technology at 6point6
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