How Intelligent Applications Can Boost Sales

CIOs can help management grow sales by proposing an intelligent application initiative. Here’s what you need to know to get started.

John Edwards, Technology Journalist & Author

July 17, 2023

4 Min Read
Woman holding smartphone with lights streaming out
Zoonar GmbH via Alamy Stock

An intelligent application is software that integrates artificial intelligence capabilities with human decision-making, leveraging the best of both worlds.

AI and humans have different, yet complementary, natures. “AI excels at handling large volumes of data, making calculations quickly, identifying patterns, and performing repetitive tasks without error,” says Joseph Ours, AI strategy and modern software delivery director at Centric Consulting. Humans, on the other hand, have capabilities such as reasoning, critical thinking, empathy, creativity, understanding context, and making ethical decisions, he notes. “By combining the wealth of experience and expertise humans bring to the table with the power of AI’s analysis and pattern recognition, intelligent applications offer businesses a powerful tool to enhance multiple aspects of the sales process.”

AI at Work

One way an intelligent app can increase sales is by creating a personalized user experience. “This focuses on offering potential customers products or services that are applicable to them specifically, based on data obtained from prior user interactions, past searches, or surveys,” says Danielle Borisovsky, a manager in intelligent automation technologies at automation firm Reveal Group.

Lead prioritization is another way intelligent applications can help spur sales. Ranking leads based on potential value and conversion probability allows sales teams to focus on the most promising prospects, Ours says. “Elements helping to prioritize leads can range from prior history, strength of relationship, size of the deal, customer monetization value, or even the maturity of your product or offering.”

Perhaps the most popular -- and valuable -- intelligent application sales tool is forecasting. “By analyzing historical sales data and various market factors, AI-powered sales applications can generate more accurate forecasts, driving better decision-making, upselling, and cross-selling,” Ours says. “AI-based systems can identify complementary products or services, prompting timely recommendations to customers and increasing revenue opportunities.”

Intelligent apps can also be constructed as data analytics models that tap into historical data and predict which products or services a specific customer may be most interested in, based on demographic information such as city, age, or gender, Borisovsky notes.

Also available are intelligent tools that automate specific repetitive, time-consuming sales tasks and processes. “These processes include data entry, generating notifications, making pricing calculations, invoice generation, forecasting analysis, and industry research,” Borisovsky says. “Automating some of these tedious tasks enable sales representatives to focus more on human-centered activities and increase their time spent to ultimately work on what they do best -- closing deals.”

An AI Sales Assistant

On the cutting edge of marketing technology are intelligent AI sales assistants, which can proactively engage with prospects, understand their unique motivational characteristics, and use collected insights to address their concerns and help them make buying decisions. Michelle Zhou, CEO and co-founder of Juji, a cognitive AI company, says that intelligent AI sales assistants are particularly well suited for high-stakes, high-value transactions, such as purchasing a vehicle or home.

An intelligent AI sales assistant should be able to help a human salesperson better read people, inferring its users’ unspoken needs and wants, likes, and dislikes, emotional cues, and personality traits, Zhou says. “The AI or the human salesperson can then use the insights to better guide prospects in their buying decisions.”

Since human sales representatives possess only a limited amount of time and energy, an intelligent AI sales assistant could actually free up time for sales personnel to connect with and collaborate with prospects and existing customers, Zhou observes.

A Team Effort

Bill Lobig, vice president of product management at IBM Automation, believes that CIOs and their sales counterparts should have just one goal in mind when evaluating any intelligent sales application: How can the technology grow the business and help it meet its revenue goals.

Business leaders must lean into their entire organization’s infrastructure and leadership, Lobig says. He advocates adopting technologies that allow employees to complete enterprise work, at an enterprise scale, without being experts in how the software actually works. “CIOs and sales leaders must have a seat at the table and seek out solutions that provide better information and, ultimately, make decisions based on data.”

IT Leads the Way

Lobig predicts a growing acceptance of intelligent applications. “For the CIO, CTO, and any operational leader who’s tasked with ensuring that their technology costs are optimized, intelligent applications proactively deliver the most efficient use of an organization’s resources while accelerating their business’ digital transformation and revenue aspirations,” he says.

CIOs play an important role in envisioning the possible, Ours says. As leaders on the forefront of technology trends, they must identify potential opportunities in which intelligent applications and AI can play a role. “Sales organizations have the primary job of generating sales, and often are not up to date on the latest technology trends,” he notes. “This is where a CIO becomes an invaluable partner.”

What to Read Next:

CIOs Must Make Call on AI-Based App Development

Digital Twin Technology: Revolutionizing Product Development

AI, Data, and Crypto in Play at Fintech Innovation Lab Demo Day

About the Author

John Edwards

Technology Journalist & Author

John Edwards is a veteran business technology journalist. His work has appeared in The New York Times, The Washington Post, and numerous business and technology publications, including Computerworld, CFO Magazine, IBM Data Management Magazine, RFID Journal, and Electronic Design. He has also written columns for The Economist's Business Intelligence Unit and PricewaterhouseCoopers' Communications Direct. John has authored several books on business technology topics. His work began appearing online as early as 1983. Throughout the 1980s and 90s, he wrote daily news and feature articles for both the CompuServe and Prodigy online services. His "Behind the Screens" commentaries made him the world's first known professional blogger.

Never Miss a Beat: Get a snapshot of the issues affecting the IT industry straight to your inbox.

You May Also Like


More Insights