12 key benefits of AI for business

1. Better decisions

Organizations increasingly use AI to gain insights into their data or, in the business lingo of today, to make "data-driven decisions." As they do that, they're finding they do indeed make better, more accurate decisions instead of ones based on individual instincts or intuition tainted by personal biases and preferences.

As an example, Kavita Ganesan, an AI adviser, strategist and founder of the consultancy Opinosis Analytics, pointed to one company that used AI to help it sort through the survey responses of its 42,000 employees. The technology analyzed narrative responses and presented summarized findings -- an approach that let company officials effectively understand what workers wanted most rather than offering them options to rank via check-the-box choices.

2. Efficiency and productivity gains

Efficiency and productivity gains are two other big benefits that organizations get from using AI, said Adnan Masood, chief AI architect at UST, a digital transformation solutions company.

Masood said AI lets organizations handle tasks at a volume and velocity that's simply not possible for humans to match -- whether they're using AI for search or to analyze data for insights, create software code or execute specific business processes.

AI not only works at a scale beyond human capacity, Masood noted, but it removes time-consuming manual tasks from workers -- a productivity gain that lets workers perform higher-level tasks that only humans can do. He pointed to the use of AI in software development as a case in point, highlighting the fact that AI can create test data to check code, freeing up developers to focus on more engaging work.

This lets organizations minimize the costs associated with performing mundane, repeatable tasks that can be performed by technology while maximizing the talent of their human capital.

3. Improved speed of business

As fast as business moves in this digital age, AI helps it move even faster, said Seth Earley, author of The AI-Powered Enterprise and CEO of Earley Information Science. "It's all about speeding up the clock of the enterprise," he said. AI essentially enables shorter cycles and cuts the time it takes to move from one stage to the next -- such as from design to commercialization -- and that shortened timeline, in turn, delivers better and more immediate ROI.

4. New capabilities and business model expansion

Executives can use AI for business model expansion, experts said, noting that organizations are seeing new opportunities as they deploy data, analytics and intelligence into the enterprise.

For example, autonomous vehicle companies could use the reams of data they're collecting to identify new revenue streams related to insurance, while an insurance company could apply AI to its vast data stores to get into fleet management.

5. Personalized customer services and experiences

AI analyzes and learns from data to create highly personalized and customized experiences and services, said Brian Jackson, principal research director at Info-Tech Research Group.

He said the most visible examples of this come from the consumer world, as streaming services, such as Netflix, and retailers use intelligent systems to study buying patterns, individual consumer data and larger data sets to determine what each customer prefers at any given time to suit their personal style, interests and needs.

However, AI delivers that personalization in numerous other areas, such as in healthcare, where it customizes treatments, and in work environments to support an employee's individual requirements.

6. Improved services

AI creates interactions with technology that are easier, more intuitive, more accurate and, thus, better all around, said Mike Mason, chief AI officer with consultancy Thoughtworks.

He cited a real estate site that employs generative AI so users can refine their property listing searches through conversational queries rather than clicking through boxes.

"The AI understands an unstructured query, and it understands unstructured data," Mason explained. In other words, the technology can analyze a user's request even when it's given in plain, conversational language; analyze all the descriptive elements within each listing, including narrative notes added by real estate agents; and present the user with a finely tuned and highly accurate list of properties that meets their requirements.

7. 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 to alert them to issues, recommend actions and, in some cases, initiate a response, according to experts.

For example, AI can use information gathered by devices on factory equipment to identify problems and predict needed maintenance. This prevents disruptive breakdowns and costly maintenance work performed because it's needed rather than scheduled.

AI's monitoring capabilities can be effective in other areas, such as in enterprise cybersecurity operations where large amounts of data need to be analyzed and understood.

8. Better quality and reduction of human error

Organizations can expect a reduction of errors and stronger adherence to established standards when they add AI technologies to processes. Furthermore, when AI and machine learning are integrated with a technology such as robotic process automation, 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.

As a result of that error reducing and higher quality, "AI improves the value prop[osition]," Earley said.

The use of AI in financial reconciliation, for example, delivers nearly always error-free results, whereas that same reconciliation when handled, even in part, by human employees is prone to mistakes.

9. 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. Moreover, AI-enabled processes not only save companies in hiring costs, but also can affect 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 to mentor employees. Additionally, AI tools can gauge employee sentiment, identify and retain high performers, determine equitable pay, and deliver more personalized and engaging workplace experiences with less requirements on boring, repetitive tasks.

10. More innovation

As workers at all levels become more comfortable and confident working with AI, experts said they're starting to use AI tools to help them be more creative and more innovative.

In her book, Ganesan described how a restaurant chain used the technology to power a mobile app that enables customers to craft their own cocktails based on their mood and food choices, with the tool concocting the recipe and then sending it to a human bartender to mix and serve.

Other industries use AI to support R&D activities, such as in the healthcare space for drug discovery work and the consumer product goods sector for new product creation.

11. Increased profitability

As they use AI in more areas of the enterprise -- from personalizing services to aiding in risk management to supporting innovation -- organizations will see improved productivity, reduced costs, higher efficiency and possibly new growth opportunities.

Taken together, that can deliver higher profitability, said Sreekar Krishna, U.S. leader of AI at professional services firm KPMG. "On the revenue side, it's potential is exponential: You can keep growing as long as you're bringing value to customers."

12. Industry-specific improvements

In addition to the benefits listed above, AI can fuel the following industry-specific improvements:

• 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, AI helps 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're also grappling with challenges. Concerns include AI bias, government regulation of AI, management of the data required for machine learning projects and talent shortages. In addition, financial gains can be elusive if the talent and infrastructure for implementing AI aren't in place.