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Theodoros Evgeniou


Preparing Your Firm for AI

To leverage AI’s transformational potential, remember that people will determine its context

Published: Tuesday, November 12, 2019 - 13:02

It seems that every week, AI technology has learned to do something humans do, but faster and better. From detecting cancers and eye conditions to predicting floods; or analyzing the language, tone, and facial expressions of candidates during recruitment processes, AI is now at the stage where it not only supports human judgment, but also makes increasingly more complex and accurate decisions.

As technology further improves and we learn how to better work and collaborate with AI, interactions between humans and computers will significantly enhance creativity—of both humans and bots.

As my colleague Serafim Batzoglou and I discuss in a recent article titled “Supercreativity,” already we’re seeing fascinating advances and possibilities in the world of art and science. AI has produced paintings, music, and poetry of undeniable artistic quality. An AI painting generated by technology recently sold at Christie’s for $432,500. Startups Aiva and Amper have developed deep-learning methods for generating music on demand and may soon enable personalized music. In the near future, the challenging and laborious process of composing and orchestrating the accompaniment to a musical theme or song is likely to be largely taken over by AI. As we note, “Creative AI may be a next milestone toward artificial general intelligence that fuels the engineering of multimodality, learned associations, and the development of effective human-AI collaboration processes.”

Meanwhile, neuroscientists and engineers recently harnessed the power of speech synthesizers and AI to develop a system that translates thought into intelligible, recognizable speech—which could lead to new ways for computers to communicate directly with the brain and, maybe more important, for us to better understand both human and artificial intelligence.

So, what does AI mean for your business? And, with so much happening at such a rapid pace, how can firms leverage AI to ensure value for their business?

Selecting the ideal AI solution

By learning from data at a fraction of the speed of humans can, AI has the ability to accomplish activities and make forecasts with incredible accuracy. As well as significantly reducing mindless and repetitive tasks, AI provides insights that can pave the way for better business decisions in all areas: budgeting and apportioning of resources, streamlining supply chains, and engaging with customers by using sentiment analysis and predictive intelligence. The transformative potential of AI will magnify during the coming decade as industries and organizations adapt their processes and even business models to take advantage of its capabilities.

Today, while increasingly recognizing the potential of AI, most organizations are in the early stages of implementing and committing to this largely unexplored technology. Even those with the most advanced technologies in place are still working out how to use it.

Investing in AI can require significant time, money, and effort. With technology heading in so many directions, it would be easy to go for the most dramatic or the most popular technology available. However, to reap the biggest benefits, organizations need to devise a solution that suits their specific needs. They must also understand that AI is not about blindly putting in place technology that replaces human resources. It is about adding value and efficiency to operations by creating smoother, faster, or more accurate processes.

When gauging the business value of an AI solution, organizations should, as always, keep in mind the basics: Consider the technology’s benefits and cost—even if these are often difficult to quantify. A good starting point is to look at the decisions the technology automates (e.g., investments, procurement, advertisement, screening and hiring) and compare this with the way the decision is currently being made. By putting a dollar amount to each decision, firms can estimate the potential value the technology could create, always keeping in mind that value is sometimes nonquantifiable.

Understanding the cost of implementing AI solutions is not so straightforward, either. Along with the cost of the technology, there are hidden costs, such as the skills that will need to be developed, the organizational changes that may be required, and potentially even updates to business models.

Implementing AI technology: a holistic approach

The adage, “IT plus an old organization is an expensive old organization” is even more relevant when investing in AI. More than any other technology, AI requires a holistic approach. It is essential for leaders to foster technological skills, IT infrastructure and governance, data literacy, an innovative culture, norms that adhere to best practices, and the ability to align the capacities of new technologies with the needs of the core business. Leaders must also consider new risks and liabilities AI can create for the business (e.g., discrimination, unfair decisions, unethical behavior of AI, even health risks), something that may prove key for executives and boards as AI is integrated into business processes, products, and services.

Although machine learning has the ability to enhance the performance of organizations, it may also present ethical and legal concerns that need to be addressed at the board level.

Identifying the quality of the solution

Measuring the quality of a solution being offered is also not easy. Many vendors will promise things that sound too good to be true because they are. However, some things that sound unbelievable will actually be true. How do you evaluate that? It is unlikely firms will have the expertise to judge the technicality of AI technology. However, what they can do is judge the skills of the people who developed it and the processes they followed. Their checklist should include, among other things, sound data quality processes; careful use of machine learning methods; people with significant experience developing machine learning solutions; and adequate monitoring processes designed to ensure that AI continuously improves, and its “behavior” remains within acceptable quality limits.

Creating strong data processes

An AI solution is only as good as the data it receives. While firms can bring in data scientists and statistics experts to verify data quality and relevance when adopting AI technology, it is important to remember that the right set of data today may be wrong tomorrow. Leaders need to focus not just on quality of data at the time of implementation, but also on the data-quality processes that are built into their organization. This will ensure that the quality and relevance of the data being used are of high standard today and into the future.

The exponential advancement of AI is set to trigger irreversible changes that will reshape business and society. Early adopters, those that gain an understanding of how AI can add value to their business and face the difficulties of integration while it is still in its infancy, will position themselves to capitalize on the opportunities as they develop. It is up to leaders to understand the capabilities, opportunities, and challenges of AI, and reorient their business to develop the core practices, skills, and processes that enable them to realize the full value the technology can bring.

First published Oct. 16, 2019, on the INSEAD Knowledge blog.


About The Author

Theodoros Evgeniou’s picture

Theodoros Evgeniou

Theodoros Evgeniou is a professor of decision sciences and technology management at INSEAD, and academic director of INSEAD elab, the research and analytics center of INSEAD that focuses on data analytics for business.