December 19th, 2019

AI: A Look Back And Where It’s Going

As the decade ends, we are witnessing a tremendous acceleration in the utility and capability of artificial intelligence and machine learning as business tools. This trend will only continue as the calendar changes from 2019 to 2020.

At DMI, our clients and partners are already seeing the benefits of using new technologies. By putting learning algorithms to work to streamline operations and develop predictive capability, using chatbots and other conversational AI technologies businesses are opening up new avenues for improving customer service. While these trends have transformative potential, they also pose thorny ethical questions that cannot be ignored.

These questions will be critical to consider in the next year and decade to come as businesses grapple with the need to improve their processes with the moral imperative to respect their customers. There are a number of areas where these questions will play out.

Retail

Retailers are using AI to automate and streamline back-office applications to improve efficiencies: to control supply chains, to connect customers to purchases, to track and predict behaviors to improve the consumer experience.

Increasingly, we aren’t just using machines as tools – we are communicating with them. We ask and they respond, just as Alexa and Siri answer our questions, customers are able to get assistance from businesses ranging from banks to their doctor from machines, who have intuitively learned how to guide people to good decisions.

As impressive as these applications are, they challenge us to know their limits – to know when a machine’s capabilities are not up to the challenge, to know when a human being must answer the questions being asked, to know the difference between information and knowledge, between data and wisdom. Failing to recognize the limitations of technology can set up both businesses and customers for failure.

In the retail sector, we will continue to use AI to streamline the customer experience. One example of this will be tightening and improving supply chain processes.

In looking at customer service, using AI chatbots can make life easier for agents. Chatbots can process information quickly, handling more requests, while prioritizing particularly challenging questions. Some applications will have customers welcoming the AI, for example, people can be more comfortable talking to a bot about personal issues they’d rather not reveal to a person. In a more common scenario, you can automate simple queries like basic product information that a bot can deliver more efficiently than a human. As our survey revealed, resistance to AI happens on a continuum. You’re much better off embracing the low-resistance end of that range.

Government 

Government agencies face challenges the private sector does not privacy regulations and public accountability chief among them. Those challenges make deploy AI in government processes complicated.

Nevertheless, agencies are launching AI pilot projects and inviting companies to compete for a chance to participate. As these small projects expand, federal agencies will gradually add more AI/ML to their technology portfolios in 2020 and throughout the decade.  DMI’s work in this area can provide a roadmap for these efforts.

Ultimately, the federal government and the private sector reach their destinations via wildly diverging routes, but they share the same desire — using thinking machines to unleash the superior power of human cognition.

Finance 

While not the public sector, the finance world provides many of the same challenges. The paramount importance data protection, the need to protect institutions from legal liabilities and stiff regulations governing transactions and data.

While AI offers potential solutions, it can be taxing to seamlessly integrate these new tools.

Data comes from multiple sources in many formats. We have to assess whether the data is accurate or producing false-positives. If inaccurate data pollutes useful data, we have to scrub out the inaccuracies.

Conclusion 

Across the board, the business environment is becoming more integrated, more connected and more dependent on intelligent machines to think and learn and provide value for companies.

DMI is committed to moving forward with our partners across a variety of sectors in ways that best suit their business models. Helping them to cede a measure of control to machines while leaving ultimate authority in the hands of humans. Our experience with machine intelligence gives us the grounding to help clients find thoughtful, humane ways to strike that balance.

We want to help leaders maximize the potential AI can bring to their businesses. By harnessing the power of machine learning and artificial intelligence, and doing so responsibly, businesses can improve their own processes and the experiences of their customers. 

 

Tags: AI artificial intelligence finance government retail

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