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How AI has become embedded in the fabric of business

A new KPMG report looks at how AI has been implemented across five industries

Ryan Deming //April 2, 2020//

How AI has become embedded in the fabric of business

A new KPMG report looks at how AI has been implemented across five industries

Ryan Deming //April 2, 2020//

After all the predictions and debates, artificial intelligence (AI) is becoming increasingly embedded in the fabric of business. That’s according to a new report by KPMG, which looks at how AI is being implemented across five industries: healthcare, financial services, transportation, technology and retail.

In the study, “Living in an AI World 2020: Achievements and Challenges in Artificial Intelligence Across Five Industries, more than 750 business insiders share their views on the future of AI in their sectors, as well as the steps they are taking to maximize its benefits and mitigate its challenges.

Key findings

While there is some variation in AI adoption across industries, there is also a depth of engagement that is highly encouraging. There were a number of notable findings:

  • While two-thirds of insiders feel AI adoption is moving at an appropriate speed within their industries, most respondents still wish their organizations would be more aggressive in adopting AI technology.
  • Most industry insiders within transportation (69%), retail (64%), technology (57%) and healthcare (52%) feel that AI is more hype than reality right now, with financial services (42%) being the exception.
  • While confidence in employees’ preparedness for AI adoption is highest among C-level leaders (79%), it is much lower among managers (38%), who are more likely to work directly with employees on a daily basis as they have a better understanding of their skill sets.

Most importantly, the report demonstrates that AI is starting to have a real impact. In fact, respondents across all industries report that AI is changing the way they do business – from improving access to medical care in the healthcare field to mitigating customer service issues in retail.

Despite this, it’s important to remember that executives at times underestimate AI’s “time to value” – or how much effort is required to implement AI and see notable results. True business value only emerges when AI implementation is tightly linked to business strategy.

AI initiatives

KPMG has supported numerous AI implementations for clients. The following are several examples of how we are working with clients to integrate AI into their business:

  • In one engagement, a banking client’s document population was too large to perform an effective manual review of their legal contracts, adversely impacting their ability to gain an actionable understanding of the risks associated with their contract portfolio. The client had to determine what types of data were most relevant to their business. We then leveraged AI to customize a process to extract the desired content from their contracts so they could perform a more effective risk assessment of their portfolio.
  • In another example, working with a telecom client, we helped a client better understand the effectiveness of customer interactions across email, phone, and chat. By incorporating end-to-end, natural language processing across various channels, the client received AI-driven insights, which enabled them to decrease the resolution time for issues across each channel and improve the customers’ digital experience.
  • We also used AI to help a government client perform an automated assessment of its asset inventory, which consisted of roadway signs and signals, by leveraging the most advanced computer vision techniques available. The client did not know how many roadway signs and signals it had in a particular geographic area, but by using AI, we helped them identify the exact geographic location of each asset.
  • For another banking/financial services client, we used a machine learning-based forecasting to improve their ability to forecast current month and annual revenue. The models incorporated both internal and external data to achieve monthly accuracy of more than 98% a full year in advance. We then integrated the models into the client’s cloud environment.

It is evident from this research and from real-world examples that we are now living in an AI world. If businesses can overcome the challenges of learning how to benefit from AI to drive real transformation within their organization, they stand to see even greater returns in the coming years.

Ryan Deming is the Director of Data & Analytics at KPMG Ignition Denver.