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3 keys for the implementation of AI in the enterprise

Organizations need to focus on diversity, proper scaling and augmentation capabilities when implementing artificial intelligence in order to keep the process pain-free.

Organizations are deploying artificial intelligence-driven technologies faster than ever today, sometimes without considering how these technologies will scale and the longer-term implications they will have on a workforce.

No matter how sophisticated or cutting-edge the technologies, the implementation of artificial intelligence can't be achieved on its own. It requires human oversight from its design to its deployment. Without the human in the loop, AI technologies -- along with the businesses that utilize them -- cannot reach their full potential.

In order to ensure humans aren't left out of the process and that the potential of AI is reached, here are three tips for business leaders when it comes to successful human-led AI integration.

1. Trade short-term innovation for long-term investment

New technologies are a dime a dozen, which makes it challenging to determine which are worthwhile investments for an organization. It's not viable to assume the latest artificial intelligence technologies are the greatest technologies or that what works for one area of a business will yield similar results for another.

For organizations to truly stay competitive and experience the full potential of what new technologies can offer, business leaders must avoid the impulse to solely invest on the basis of short-term returns and instead focus on the longer-term business impacts. AI is about more than reducing costs through efficiency and automation. Enterprises are finding it can play an important role in long-term strategic initiatives.

A recent report cosponsored by EY revealed that financial services organizations are moving away from using AI for just cost reduction purposes and are using it to generate new revenue streams, manage risk and facilitate client acquisitions. Businesses that focus their AI system integration strategies on solving long-term challenges and place humans at the center of the strategy are positioned to see the best ROI.

AI winters
Though AI has gone through winters, it continues to advance and has become a near necessity in the enterprise.

2. Don't assume AI system integration and automation eliminate the need for the human enterprise

Many assume that, when businesses implement technologies like AI, jobs will be displaced. The reality is: Roles will continue to evolve, and the nature of work will change. Technology, by itself, is never the solution; it requires human intervention and oversight. In fact, when organizations deploy AI technologies thoughtfully, it can help reduce employee turnover and increase job fulfilment, and therefore, humans stand to benefit.

In these use cases AI can augment humans in their current roles rather than replace them. As long as the available data is of high quality, then the machine learning algorithms, the predictive analytics, as well as the customer service applications can improve employees' day-to-day experience. 

At EY, we use AI technologies to process, review and evaluate all sorts of business documents. When we first piloted the use of AI to help read and interpret lease contracts, we were three times faster and more accurate than our manual process. Our teams were able to complete engagements in minutes, as opposed to hours, which enabled them to spend more time on higher-level thinking, providing better insights and solving more complex business challenges for clients.

In circumstances such as this, there was immediate and long-term business value added through the augmentation of employees with artificial intelligence. 

3. Champion diversity to enable productivity

While many companies find value in diversity and have invested in relevant initiatives, what some don't realize is that it's not just a cultural perk. In reality, more diverse organizations tend to be more innovative and higher performing. The reason for this is that a diverse workforce enables many different perspectives to be considered, represented and discussed when organizations are working to identify challenges, develop solutions and implement those solutions strategically.

A great example of this is the EY Neurodiversity Center of Excellence, which matches roles in technology with people on the autism spectrum -- an often overlooked talent pool that frequently excels in some of the math and technology skill areas that underpin innovation. EY teams reported increased productivity and improved communications as a result of the program. Neurodiverse individuals also will be supporting EY's AI engineering teams this year.

Without greater diversity, we risk programming biases in the artificial intelligence technologies humans help create. These biases not only prevent AI from working properly and reaching its full potential, but they also further amplify biases and inequalities we seek to solve. This is where humans have a central role in ensuring AI technologies are behaving appropriately.

Put simply, companies that are in the midst of the implementation process of AI and emerging technologies should not solely seek to increase efficiency. These technologies are meant to foster collaborative environments where diverse humans are working to their full potential and adding long-term value to the organizations they're associated with -- and to each other. As technologies continue to be created and evolve and as businesses determine how to best implement them, strategies that pair technology with human knowledge and expertise will yield a truly innovative approach and position businesses well for long-term success.

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