AI: 4 questions companies should be asking

Artificial intelligence (AI) is often assumed by corporate executives to be the wave of the future – and to have enormous potential for enhancing profits. To many business leaders, the return on investment of AI technologies seems a foregone conclusion. But that assumption can be a mistake.

The gap between expectations and reality

A study conducted last year by Cognizant Digital Business indicated roughly two out of every three executives foresee significant financial benefits for their companies from AI. However, the same study found that only 15 percent of executives were aware of their organizations having fully implemented AI projects, with most such projects still in planning or pilot stages. What explains this disconnect between awareness of AI’s importance – and optimism about its potential – on one hand, and time it takes to scale up implementation on the other?

One other key finding of the Cognizant study was that the reasons offered by executives for investing in AI remained vague, amounting to an “all-of-the-above” selection rather than a focus on specific issues and goals. Such an approach seems to correlate with projects becoming stalled or reversed, as senior leaders soon lose interest and AI initiatives fall victim to budget cuts and death by indifference. What this amounts to is a paradox in which the technology almost universally deemed crucial to future business success is, when broken down into individual projects, fails to deliver on it’s potential.

To avoid the contradiction of AI enthusiasm coupled with AI frustration, leaders need to think more in-depth about how AI is going to transform their businesses and generate profits, rather than merely assuming it will. This entails asking four key questions about AI implementation and the end goals of digital transformation.

Does your company have an AI strategy?

One of the consequences of lack of awareness on the part of senior executives of AI technologies is the delegation of initiatives to IT departments and tech experts. Obviously, these experts are crucial to the research and development of AI projects, but such endeavors are less likely to succeed if they are not motivated by an over-arching vision of how they will create value for the company. Focusing on the algorithms and technologies being developed and how they can cut costs within certain departments mistakes the trees for the forest. The real question should be ‘What is our AI strategy, if we have one?’ And a strategy focused solely on automating tasks to improve the bottom line misses out on the most innovative uses of AI to differentiate by enhancing customer service, employee experience and high-level decision-making.

Whatever a company’s AI strategy is, leaders must ensure coordination of projects and alignment with core business strategies rather than seeing AI as an IT functionality. In an era when AI seems to the non-technical person as almost magical in its capabilities – ranging from digital assistants that can understand human emotions to self-driving cars and aircraft – it is easy to become focused on this magic rather than on the actual return and value creation to the company. The fact remains that not understanding how AI is being applied and the strategy behind it will lead to an organization falling behind and failing to differentiate itself from competitors with more coherent approaches.

Do you have sound AI governance structures?

Whether it is self-driving cars failing to avoid pedestrians or facial-recognition technologies perpetuating racial bias, there are controversies aplenty when it comes to still-evolving AI applications. But while these stories are widely reported and known, the non-technical employees of organizations (senior leaders included) are often blind to the potential pitfalls in their own projects.

Therefore, organizations wishing to successfully implement an AI strategy must ask themselves if their governance structures for overseeing, modifying and (if necessary) terminating AI programs are sound, if they exist at all. If a company is using AI to its full potential, that use will include improving interface with customers, employees and partners, in addition to making key decisions. That requires human oversight of all applications, ensuring trust and transparency that prevents machine learning from running amok. The consequence of not having the right governance structures and transparent oversight is potentially seeing an enormous setback for ROI, no matter how amazing is the technology or algorithm itself.

Are you creating and maintaining responsible AI applications?

Even proactive governance and oversight policies will not have their desired impact if responsibility, ethics and human-centricity are not at the forefront of developing and deploying AI applications. The controversies which surround issues like bias AI are the result of a tech-centered approach which discounts how algorithms and technologies will impact individual stakeholders – whether customers, employees or leaders who increasingly rely on AI to make decisions.

That is why an AI code of ethics is essential to an organization’s strategy and should be embedded into every stage of projects from initial development to deployment and governance. Failing to do this can drive customers away, offend employees (causing major HR problems) and invite regulatory scrutiny, severely raising business costs and reducing – if not eliminating – AI’s ROI.

Is culture part of the strategy?

An AI strategy will fail to yield results if it does not take culture into account. Success depends on considering the impact of AI on all roles within an organization, from the call center employees to analytics leaders to the end users themselves. How will this transform not only these people’s tasks and experiences, but the way they operate and their how they make decisions? Employees will have to develop the means to scrutinize AI decision-making and not simply accept it as automatically the best solution, keeping ethics and the potential for AI to make inaccurate or biased judgements in mind as well. Failing to appreciate – and implement – the cultural transformation which AI requires can quickly erode its value to the organization.

To get ROI on AI, think about the ‘big picture’

These four questions are the starting point for realizing the full benefits of AI for organizations. The correct approach is neither seeing AI as a magical but mysterious solution to all a company’s problems and an elixir for exponential growth, nor a purely utilitarian means of cutting expenditures in this or that department.

It is a company-wide transformation, necessarily involving every branch of the organization and fully understood, coordinated and directed by senior leaders, with the aim of improving the way customers and employees are engaged and the way managers implement plans. Executives who grasp these fundamentals can drive transformation successfully and responsibly – and get ahead of competitors in an increasingly fast-paced and winner-takes-all landscape.

Bret Greenstein is global vice-president and head of Cognizant’s digital business AI practice, focusing on technology and business strategy, go-to-market and innovation helping clients realize their potential through digital transformation.

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