Artificial Intelligence in practice: Redefining success with AI for business
Published Date: February 1, 2024
In recent years, the rapid advancement in artificial intelligence has led to a steady rise in adoption and increased reliance across industries. Today, many of the world’s biggest organizations are no longer questioning the role of AI for business but focusing on how to scope, deploy, and scale it quickly to fully realize its value and benefits.
But as is the case in adopting any new or disruptive technology, organizations need to see through the hype and focus on its business capabilities. As such, the questions that organizations should be asking are: What are the areas where AI can truly make an impact in our business? Can AI satisfactorily address our business needs? Will implementing AI now allow us to see significant returns quickly?
AI matched to your needs
Broadly speaking, companies use AI to support three fundamental business needs: process automation, cognitive insight, and cognitive engagement.
- Process automation. Unlike earlier business-process automation tools, AI can automate digital and physical tasks. This is particularly true for back-office administrative and financial activities, which AI can handle in much the same way as a human does—by encoding, gathering, and processing from multiple IT systems. Tasks that organizations can address via process automation include reconciling failures to charge for services across billing systems, extracting provisions out of legal and contractual documents, and transferring information from email and call center systems into system of record.
- Cognitive insight. AI uses algorithms to detect patterns in large data sets and interpret their meaning. In contrast to traditional analytics, cognitive insights from AI are usually more data-intensive and detailed. The models are trained on part of the data set to make them more contextually relevant, and the models “learn” and improve over time. Examples of cognitive insight applications in business include automating personalized targeting of digital ads, identifying credit fraud in real time, detecting insurance claims fraud, and predicting customer purchase behavior.
- Cognitive engagement. AI analyzes historical data on customer preferences, tastes, and expectations to provide rich, personalized experiences for individual customers at an unprecedented scale. Through the use of natural language processing chatbots, virtual assistants, and intelligent agents, organizations can address a broad and growing array of issues. These capabilities include addressing password requests and technical support questions, creating internal sites that answer employee questions on benefits, HR policy, and IT; it also helps healthcare providers create customized care plans that take a patient’s medical and treatment history into consideration.
Depending on their needs, organizations may choose to use one type or any combination of all these AI applications.
As familiarity with AI and cognitive tools grows, trends show that the use of AI in business is dramatically shifting. From small, use-case specific applications, organizations are now placing AI at the strategic core of their operations to reap its full benefits.
From hype to real impact
Despite being relatively new, AI has already differentiated itself from the dot-com era, blockchain hype, and other tech bubbles of the past by delivering immediate, tangible results.
In 2017, a Deloitte survey found that 83 percent of their respondents have already achieved either moderate (53 percent) or substantial (30 percent) benefits from their work with cognitive and AI technologies, with more frequent AI deployments resulting in increased returns. Fast forward to 2022: A survey reported that 42 percent of over 1,600 C-suite executives and data science leaders from the world’s largest organizations said the return on their AI initiatives exceeded their expectations. This finding aligns with another survey of senior data and technology executives from the same year, where 92 percent of large companies reported achieving returns on their data and AI investments—an increase from 48 percent in 2017.
A look at AI’s business impact
Owing to its flexibility and broad utility, AI leads to many positive outcomes for businesses and enterprises across different industries. These benefits range from increased productivity, enhanced customer engagement, and reduced costs, to mitigated risks and better decision-making.
- Increased productivity. AI allows workers to finish pending tasks in less time and focus on more important tasks by automating routine operations. By using AI chatbots, that generate automated responses to repetitive customer queries, businesses can boost their response time and engage customers with little to no human involvement.
- Enhanced customer engagement. AI helps retailers curate product and service recommendations that increase engagement, lead to sales conversions, and improves customer retention over time. In marketing, AI is used to create compelling and relevant content tailored to different audience segments and deliver personalized experiences that feel more authentic, enjoyable, and meaningful to customers.
- Reduced costs. In manufacturing, AI supports human inspectors through visual inspection technology to detect defects, shorten inspection times, and minimize recalls and rework, thereby saving costs
.By optimizing delivery routes using real-time forecasts and continuous estimation, AI not only helps logistics companies save on vehicle maintenance costs but also improves fuel efficiency and reduces delivery times.
- Mitigated risks. AI can strengthen a business’s security network by detecting bugs, addressing cyberattack risks and notifying leaders about malicious attempts to break into company data. In banking and finance, AI can monitor network traffic and transactions in real-time to detect anomalies, fraudulent activities, and potential threats.
- Better decision-making. To ensure supply meets demand, AI helps manufacturers harness data from their equipment and workflows to quickly identify trends and generate a more accurate forecast. In retail, AI can predict stock requirements based on sales trends, seasonality, and other factors. This allows retailers to save money by optimizing stock levels and capitalize on opportunities by avoiding stockouts.
Early adopters see early returns
With data stacking up in favor of AI for businesses, organizations that delay adoption are putting themselves at a disadvantage. For one, increased worker productivity, higher revenue, improved operational efficiencies, and other AI benefits take time to materialize. Additionally, pioneering in this space is a competitive differentiator that can significantly affect customer perception. Technology trailblazers, perceived as risk-takers to enhance customer experience, enjoy a more positive reputation. Finally, early adopters can redefine, influence, and shape their industries, enabling them to become thought leaders.
The advantages of early AI adoption extend beyond the intangibles. In a 2023 study by LTIMindtree, early or extensive AI adopters saw increased revenue—80 percent of leaders report at least 5 percent growth—and cost savings up to 40 percent.
Boost your business outcomes with the right AI partner
For many organizations, there is a great urgency and an equally immense incentive to be one of AI’s early adopters. However, getting into AI is not as simple as installing new software and hardware. Successfully implementing AI across the business hinges on many factors, and investing in it doesn’t automatically guarantee massive returns. As such, organizations shouldn’t jump into AI blindly.
At XURPAS AI Lab (XAIL), we help organizations make the right AI choices by looking at them from their context and perspective. We make sure that the AI tools and solutions that they are considering for their business align with their needs, goals, resources, and capabilities.
If you’re ready to start leveraging AI for your business needs, get in touch with our experts today.