Top AI Use Cases and How to Leverage Them for Productivity

Dan Ortiz

Organizations are entering a time of unprecedented disruption. Amid a growing talent shortage, 75% of CEOs are struggling to fill open roles—and they’re increasingly turning to AI to fill the gaps. AI tools can analyze vast amounts of data in real-time, draw insights, and make intelligent decisions by acting within parameters laid down by human leadership. More than 85% of organizations expect to build AI into their operations in the next five years.

To use AI to increase your company’s efficiency, don’t think of it as a way to replace entire jobs. Instead, map your processes to unearth toil—or manual, repetitive, automatable work that customers won’t eventually pay for.

For instance, let’s say you have a bookkeeper on your payroll who spends an hour each day categorizing expenses and looking for discrepancies. AI can easily replicate that workflow, freeing up your human employee’s time to work on higher-level tasks. AI can take over job duties like:

• Data entry
• Answering customer questions
• Resolving support issues
• Screening resumes
• Reviewing and summarizing documents
• Conducting research
• Generating reports
• Data manipulation

Here’s a look at the most common AI use cases and how to leverage them for business productivity.

IT Automation

A 2023 report by the World Economic Forum revealed that 75% of organizations are struggling to retain skilled IT workers. As the pace of innovation and remote work increase, IT teams are drowning in a sea of toil.

To combat the crunch, companies are using AI to automate dozens of labor-intensive IT tasks, including system monitoring, anomaly detection, predictive maintenance, cybersecurity threat detection and response, network optimization, and IT service management. AI is also widely automating routine helpdesk inquiries through chatbots.

In a real-world example, commercial real estate firm CBRE was drowning in billions of data points from their worldwide operations, and IT teams were struggling to keep pace. They developed a comprehensive AI-driven data platform that enables advanced analytics, delivering deep insights that help them make more informed decisions and have improved their client service scores.

Product and Service Innovation

The creative process is clogged with time-consuming, repetitive tasks. Product and service development teams can improve their efficiency as much as 40% by leveraging AI.

A big part of any product manager’s job is sorting through mountains of company data to guide design teams. For example, what are customers saying about previous product versions? What features would your sales team like to see in the next release? What insights are hiding in your safety or security data that your engineers should be aware of? AI can make short work of this trove of information, accelerating the discovery process keeping designers from re-inventing the wheel.

Mastercard is using AI to innovate its payment resiliency. “In today’s world where the payment ecosystem is highly distributed and increasingly complex, it’s vital banks get the support they need to ensure card payments run seamlessly,” says Ajay Bhalla, President of Cyber and Intelligence at Mastercard. AI tools now make intelligent decisions to keep their card networks up and running longer, with fewer outages.

Infographic: Top Use Cases for AI

Fraud Detection and Cybersecurity

Cybercrime sets new records every year, with a projected cost of $10.5 trillion in 2025—almost half the size of the entire U.S. GDP. This staggering growth comes as an increasing share of world business is conducted online. One of the biggest reasons for the problem is a lack of resources, combined with the sheer size of the Internet—at roughly a trillion gigabytes and five billion users.

While human cybersecurity teams can’t begin to police an arena of this size, AI can be everywhere at once. AI can monitor networks in real-time with zero downtime, detect anomalies, and generate reports for human cybersecurity professionals. Global tech leader Siemens now uses AI to process 60,000 cyberthreats per second, taming their 300% increase in annual attacks. A team of less than twelve human cybersecurity experts manages their AI cyberthreat detection system.

Microsoft Copilot for Security can summarize incidents, perform impact analysis, reverse-engineer scripts, and conduct several otherwise time-consuming security tasks.

Automating Business Processes and Workflows

About 38% of organizations are already using AI to transform their business processes. Most organizations face the wastes of overproduction, excess inventory, defects, wasted motion, overprocessing, waiting, and unnecessary transportation. These are the wastes Taiichi Ohno and Shigeo Shingo famously attacked in the Toyota Production System. Some companies are turning to AI to help identify and remove those wastes. Financial service firm Credigy Solutions used AI to automate the due diligence reviews of their loan documents. Manufacturing company Horizon Global implemented an AI data entry system that raised their data entry accuracy to 99%, delivering a 20% decrease in processing waste.

How to Implement AI Automation

Building AI into existing business processes and workflows may seem like a daunting task, but organizations can reap massive rewards by starting small. 

  • Find the right AI use cases: Identify processes in your operations, workflows, and teams that are human-intensive, data-intensive, highly repetitive, and/or need natural language interaction. Data-first problems often have useful AI solutions.
  • Set objectives: Estimate measurable improvements and decide on project KPIs.
  • Select tools: Organizations can realize immediate benefits from AI with out-of-the-box tools like Copilot for Microsoft 365 and ChatGPT. These tools can assist with dozens of job functions, including automated data analysis and report generation in Excel, analyzing customer feedback, and fast data visualization.
  • Create safeguards: Build guardrails to prevent AI from leaking organizational data, such as screening or validation to ensure a custom GPT doesn’t reveal sensitive company information.
  • Start small: Define success in phases with bite-sized wins to show initial ROI.
  • Test and expand: Institute a continuous improvement process to support change-management plans, including employees via feedback loops.
  • Win buy-in: Ensure organization-wide buy-in and train your employees to use new AI tools. Include adoption management, with champions to support employees and ensure the tools are being used effectively.

Equip Your Teams to Leverage AI

Connection can help you decide on the most productive embedded AI solutions to deploy, and then smoothly integrate new AI technology and solutions into your workflows. We can also help:

• Power your teams to collaborate seamlessly across on-site, remote, and hybrid environments
• Create out-of-the-box experiences for end users without compromising quality and speed
• Implement advanced capabilities, responsiveness, and support that are second to none

Explore our AI solutions and Digital Workspace services today by contacting an expert at 1.800.998.0067

With over twenty years of experience in the software industry, Dan began his career as a technical sales specialist, concentrating on mobile device form factor aggregation. Currently, he leads Connection’s Digital Workspace Center of Excellence, where he is dedicated to bringing innovative new solutions and services to market to best serve customer needs. Dan has held various presales roles, where he excelled at identifying strategic initiatives with customers and turning them into reality, always considering both long- and short-term goals with a phased approach. For the past decade, his focus has been on cloud-based transformation, helping customers revolutionize their business practices. He has led presales teams specializing in Multi-cloud and Digital Workspace solutions. In his spare time, he enjoys spending time outdoors hiking, kayaking, and engaging in physically challenging adventures.

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