As businesses continue to deploy artificial intelligence technologies within their operations, they are starting to reap tangible benefits, including material gains.
The 2020 Global AI Survey from McKinsey & Co. reported that 22% of companies using AI said the technology accounted for over 5% of their 2019 earnings before interest and taxes. Additionally, revenue generated by AI increased year over year in the majority of the business functions using AI technologies. Companies earning the most from AI told McKinsey they planned to increase their AI investments in response to the COVID-19 pandemic.
Business process efficiency tends to top the benefits cited by enterprise users (see below). But the value business leaders seek to gain from AI shifts depending on a company's maturity in using AI technologies, according to Deloitte's latest "State of AI in the Enterprise" report: While AI "starters" ranked lowering costs second to process efficiency on a list of AI benefits, "seasoned" AI users prioritized creating new products and services.
Here are seven important benefits AI brings to businesses and some industry-specific examples.
1. Efficiency and productivity gains
Efficiency and productivity gains are two of the most-often cited benefits of implementing AI within the enterprise. The technology handles tasks at a pace and scale that humans can't match. At the same time, by removing such tasks from human workers' responsibilities, AI allows those workers to move to higher-value tasks that technology can't do. This allows organizations to minimize the costs associated with performing mundane, repeatable tasks that can be performed by technology while maximizing the talent of their human capital.
"CIOs need to see where AI can help functions do more with less time and less resources, so they can [enhance] the experience for employees and users alike," said Beena Ammanath, executive director of Deloitte AI Institute.
2. Improved speed of business
As fast as business moves in this digital age, AI will help it move even faster, said Karen Panetta, a fellow with the technical professional organization IEEE and Tufts University professor of electrical and computer engineering. AI enables shorter development cycles and cuts the time it takes to move from design to commercialization, and that shortened timeline in turn delivers better, and more immediate, ROI on development dollars.
3. New capabilities and business model expansion
Executives can use AI for business model expansion, said Chris Brahm, senior partner at Bain & Company, and leader of the firm's global Advanced Analytics practice.
"As you deploy data and analytics into the enterprise, it opens up new opportunities for businesses to participate in different areas," he explained.
For example, autonomous vehicle companies, with the reams of data they're collecting, could identify new revenue streams related to insurance, while an insurance company could apply AI ton its vast data stores to get into fleet management.
4. Better customer service
Delivering a positive customer experience has become the price of doing business, said Seth Earley, author of The AI-Powered Enterprise and CEO of Earley Information Science.
"We're trying to embody everything we know about the customer, the customer's needs, our solutions and the competition and then present to the customer what they need when they need it," Earley said. "If we had a salesperson who could do that for everyone, that would be great, but we don't."
AI, however, can do all that and more, leading to more customized and personalized interactions between organizations and each individual customer.
5. Improved monitoring
AI's capacity to take in and process massive amounts of data in real time means organizations can implement near-instantaneous monitoring capabilities that have the capacity to alert them to issues, recommend action and, in some cases, to even initiate a response, Ammanath said.
For example, AI can take information gathered by devices on factory equipment to identify problems in those machines as well as predict what maintenance will be needed when, thereby preventing costly and disruptive breakdowns as well as the cost of maintenance work performed because it's scheduled rather than because it's clearly needed.
AI's monitoring capabilities can be similarly effective in other areas, such as in enterprise cybersecurity operations where large amounts of data needs to be analyzed and understood.
6. Better quality and reduction of human error
Organizations can expect a reduction of errors as well as stronger adherence to established standards when they add AI technologies to processes, according to Madhu Bhattacharyya, managing director and global leader of Protiviti's Enterprise Data and Analytics practice. When AI and machine learning are integrated with a technology like RPA, which automates repetitive, rules-based tasks, the combination not only speeds up processes and reduces errors but can also be trained to improve upon itself and take on broader tasks.
The use of AI in financial reconciliation, for example, would deliver error-free results whereas that same reconciliation when handled, even in part, by human employees is prone to mistakes. "Can you maintain better quality with AI? Yes, you can," Bhattacharyya said.
7. Better talent management
Companies are using AI to improve many aspects of talent management, from streamlining the hiring process to rooting out bias in corporate communications. Writing about the growing use of AI in recruitment, independent consultant Katherine Jones said AI-enabled processes not only can save companies in hiring costs but also impact workforce productivity by successfully sourcing, screening and identifying top-tier candidates. As natural language processing tools have improved, companies are also using chatbots to provide job candidates with a personalized experience and mentor employees. Additionally, AI tools are being used to gauge employee sentiment, identify and retain high-performers, and determine equitable pay.
In addition to the benefits listed above, AI can fuel numerous industry-specific improvements. Here are three examples, from Shervin Khodabandeh, a managing director and senior partner at Boston Consulting Group and co-leader of its AI business in North America:
- Retailers can use AI to better target their marketing efforts, develop a more efficient supply chain and better calculate pricing for optimal returns. At retail companies where humans do the majority of the work, AI will help predict customer requirements and appropriate staffing levels.
- The pharmaceutical sector can use the technology to perform drug-discovery data analysis and predictions that can't be done with conventional technologies.
- The financial industry can use AI to strengthen its fraud detection efforts.
It's important to remember that as companies find ways to use AI for competitive advantage, they are also grappling with challenges. Concerns include AI bias, government regulation of AI, managing the data required for machine learning projects and talent shortages. In addition, financial gains can be elusive if the talent and infrastructure for doing AI are not in place, according to research done by MIT Sloan Management Review and Boston Consulting Group.
Read about the major risks associated with AI in this article.