How to successfully bring AI into your enterprise
While artificial intelligence (AI) has been creating buzz in enterprise for the last few years, many companies and organisations are still hesitant to consider adopting AI. With a lot of uncertainty surrounding its function and need in business, many CTOs and CIOs still struggle to gain approval from the board to invest in the technology.
The adoption of AI
Much of the hype surrounding AI comes from its potential to revolutionise the workplace. While there is a great deal of experimentation ongoing, there has been little actual full-scale implementation of AI across businesses. While platform companies such as Amazon and Google are leading investment into the research and development of AI to make it more accessible, many executives are struggling with the decision on whether AI is suited for the business and will provide good value for money.
It is difficult to measure returns on investment with AI projects as traditional methods of calculating benefits simply don’t work. Currently, companies are conducting projects that are optimising AI for specific advancements, including developing computing and algorithms to optimise last-mile logistics, routing, risk management activities and financial crime monitoring.
Beyond traditional obstacles when adopting new projects – significant costs, huge time commitments and internal staff requirements – AI has two key problems that have made it difficult to land in enterprise.
Firstly, traditional businesses were set up to transact, not curate data. This historic lack of data curation means there is no data that can be used to generate training data. The lack of understanding of this point has significantly slowed the process of mainstream adoption of AI.
Secondly, there is a prevailing culture of short-term results in enterprise which has clouded the thinking around investing in long-term transformations. AI is a programme of investment over years and is not a quick fix for the next quarter’s return. Beyond tooling and experimenting, there is little real investment in enterprise AI.
In addition, many large enterprises have their own in-house teams that haven’t delivered the goods when it comes to actually implementing AI in a real enterprise environment.
Key cultural changes needed
The concept of ‘test and fail’ will be key in successfully introducing AI into enterprise. AI requires a culture where failure is tolerated which is counter to the traditional IT-oriented culture. By adopting a trial and error approach, AI algorithms can be refined and improved constantly, ultimately providing the best investment return.
The risk factor associated with adopting AI is also an obstacle holding back enterprise adoption. Both the private and public sector tend to think only three months ahead and would rather do nothing than gamble with their jobs – the average tenure of a CIO is now measured in months rather than years. Changing this behavioural attitude will be essential if businesses want to be at the forefront in adopting innovative technology and stay ahead of competitors.
Businesses which have already funded digital transformations, and received little return, are less inclined to bet on the ‘latest fad’ of AI. However, AI holds much promise to bring genuine transformations to a business. Organisations that embrace ‘test and fail’ will learn quickly, embrace the wave of disruption coming and experience the benefits of AI in future business.
AI will greatly improve the business-customer interaction and add significant value to the relationship. We’ve already seen AI being used in chatbot software, which has helped move the task of dealing with customer inquiries away from IT staff who can then focus on IT management. The most important aspect of AI is that it gets smarter over time – making decisions better and faster than before – and will continue to offer value to the business in the future.
Ultimately, AI will become fundamental to how business is done. The future will see an AI arms race based on who can optimise the collection of mass training data, AI platforms and AI talent, and ultimately apply the means of great AI to solve and optimise business transactions first. The use of AI in wide-scale enterprise will increase competitiveness, ensure compliance and decrease costs – the main business benefit will therefore be survival.
The question businesses now face is how to create an investment programme for AI that is focused on the longer term, and how to change the organisational culture to lean into AI. Paradoxically, the real innovation in AI will come from making businesses ready to adopt the technology, not the actual training and implementation of AI, which is becoming ever more commoditised.