6 Ways to Use AI at Work

AI can save time and money and help employees across industries spend more hours creating and innovating. Here are 6 popular ways to use AI at work today.

As AI matures and users explore new ways to use the technology, it’s growing into a widely used tool that can reduce mundane tasks, tackle large datasets, automate repetitive work, and more. For humans, incorporating AI at work can save time and resources better spent on new ideas and innovation.

With more AI platforms available than ever, and with models becoming more sophisticated, there’s a lot of room for exploration, experimentation, and growth with AI technology. Businesses are already incorporating AI to make better use of their data for decision-making, analytics, reporting, and more. 

Using AI at work promises gains in productivity and creativity, and there’s more to come — it’s still early days for this technology. While 92% of companies plan to increase their AI investments over the next three years, according to McKinsey, just 1% of leaders call their companies “mature” on the deployment spectrum. “Mature” for AI deployment means that AI is fully integrated into workflows and drives substantial business outcomes.

As users become more comfortable and skilled with writing prompts and incorporating AI into their work, they’re discovering new possibilities. Here are some popular ways to use AI at work — with lots more continually emerging.

1. Automating workflows for speed and reduced repetition 

Plenty of employees have to complete repetitive tasks as part of their job, such as data entry, invoice processing, approval processes, and other paperwork. Tasks like taking and disseminating meeting notes, checking content for adherence to search engine requirements, and more can be automated. Any rule-based task can be automated with help from AI, with prompts refined as needed to create the right workflow. AI can save hours of time in this way, offering a major productivity boost. AI can incorporate ML, natural language processing, and predictive analytics to automate workflows, including humans as needed, such as to approve certain actions.

At Toyota Motor Company, for example, they implemented AI-powered predictive analytics, adding sensors on production equipment to monitor temperature and other performance metrics. The AI predictive maintenance platform identified patterns to flag possible equipment failures before they happened.

2. Serving customers on the front line 

AI agents have been deployed to answer and triage customer service calls in many industries. IT departments in particular can easily be overloaded with user questions and issues, leading to service ticket backlogs. Users can typically contact IT on multiple channels and often bring the same questions, such as asking for password reset or software license. It’s common for IT teams to constantly work to catch up with issues, without time to stay ahead of challenges and do proactive work. 

Atera’s IT Autopilot is an AI agent that serves end users across email, chat, and a customer portal, answering questions, offering guidance, and taking action on its own. IT Autopilot handles both routine and complex tasks, and when it can’t solve an issue, it sends the ticket to the IT team. Our internal data found that IT Autopilot can resolve up to 40% of the IT workload autonomously without needing IT staff — 80% of your tier 1 tickets. 

3. Personalizing customer communications 

Personalization is expected today in many use cases, and AI’s capabilities make it possible. For marketers, for example, AI can segment audiences based on customer data on demographics and purchase history, then create tailored content and recommendations. Amazon recommends products for customers with AI assistance, while Sephora’s app uses AI to offer personalized beauty recommendations based on skin tone and style.

4. Turning data into answers 

AI can search through large volumes of data much more quickly than humans, opening up many potential use cases across industries. With accurate data insights, businesses can make better data-driven decisions faster, and take advantage of their own proprietary data for unique insights. 

AI tools can analyze large datasets of all types to find trends and generate reports and visualizations. Businesses like law firms or research organizations can put AI to work to analyze documents, extracting specific information to build tables, charts, or quick summaries. Other unstructured data, like customer interactions, can be parsed with help from AI to find patterns or trends, such as whether customers are happy with their purchases or finding the answers they need. These AI uses can retain institutional and historic knowledge as well as saving time and offering better data points for decision making.

5. Augmenting skilled human capabilities

IT departments are putting AI tools to work for repeatable, commonplace tasks, helping to extend the skills and capabilities of team members. Atera’s AI Copilot, for example, is designed to offer intelligence assistance to users for managing devices, resolving tickets, and handling alerts. It’s a single product that can save tremendous amounts of time and serve users much faster with accurate, timely information.

AI Copilot can turn simple instructions into powerful scripts without requiring any coding, which is useful to automate maintenance tasks and more. It can also generate and execute commands on a device, plus uses natural language search to find and manage devices. And end-user queries in tickets can be answered reliably with AI Copilot’s responses. IT teams can save lots of time generating knowledge base articles from resolved tickets with Copilot, as well as summarize tickets to learn for future questions.

6. Building custom models for typical problems

AI users in many industries and teams likely solve similar problems over and over again. That might be filling in paperwork correctly, complying with industry standards, ensuring consistency across products, and managing complex supply chains. Any business can start with a pre-trained, out-of-the-box model, then train it on company-specific data to create a fine-tuned system. These existing LLMs can be specialized for particular tasks, with different models handling different tasks. As AI platforms start to include reasoning capabilities, AI will have more capacity for complex decision making and the ability to create step-by-step plans to achieve goals. Users will be able to fine-tune reasoning models and integrate them with company- or domain-specific knowledge for even better accuracy and sharper data insights.

Bloomberg’s BloombergGPT, for example, is a financial LLM trained on proprietary financial data. It’s able to save employee time and equip finance professionals by generating reports, analyzing financial data, making market trend predictions, creating market summaries, and analyzing sentiment.

Transform work daily with new ideas and AI  

AI tools have made an impact on workplaces already, with teams and workers coming up with new, unique ways to use the technology. To use AI intelligently at work, start by identifying some time-consuming, data-intensive processes to automate with AI and show some quick ROI wins. Get to know whether integration or data quality is an issue before developing further workflows. 

Of course, not every worker curious about AI wants to train models or develop new prompts and projects. Options like Atera’s AI tools, Copilot and Autopilot, can automate workflows and reduce the burden of administrative tasks for IT departments. For IT teams and others trying to be more productive and free up time for creativity, AI can serve as a fast-moving assistant.