Generative AI transforms workforce productivity by automating tasks, boosting creativity, enabling personalization, and driving data-driven decisions. We explain how in this blog.
Using generative AI (GenAI) in the workplace has sparked an explosion of creativity and innovation, spreading through the business world at breakneck speed. However, this technology’s potential is so diverse and far-reaching that it can be hard to nail down exactly how to use AI to benefit your business.
For many organizations, the most logical use case is productivity. Here’s a breakdown of what generative AI is, examples of how to use it to boost productivity, and some things to keep in mind as you move forward.
Here are a few important takeaways you’ll learn in this blog:
- GenAI can automate repetitive tasks, such as data entry, because it can read and classify data from PDFs and other documents.
- You can use a GenAI system to read and analyze customer data and then personalize their future experiences.
- GenAI can analyze sets of data, identify trends, and use its analysis to help you make decisions.
- It’s crucial to consider ethical issues, such as the fear of job displacement, data stewardship concerns, and keeping your solution and usage plans transparent.
Where Generative AI Fits Into the Workplace
Generative AI is a branch of AI that mimics human words, speech, art, designs, coding, and other creations. Trainers or software create input that trains a GenAI system, which recognizes patterns and then uses these patterns to generate output like what a real human would produce.
One of the most widely known examples of GenAI is the GPT model. These models identify patterns and use them to produce outputs similar — or better than — what a human could produce. For instance, a GPT model can write a full book that reads relatively well and includes plot twists and other literary devices. They can also write code and design entire websites.
GPT models and other GenAI are widely used in industries such as:
- Finserv, where GenAI handles customer inquiries and answers questions about accounts
- Insurance, where companies use GenAI to analyze documents and then predict risk
- Healthcare, where a GenAI system can analyze patient symptoms or lab results and suggest possible causes
- Energy, where GenAI systems can create invoices and process customer payments
- Manufacturing, where companies use GenAI to predict customer demand for certain goods
One of the most common use cases for AI in the workplace is accelerating innovation. Programmers often use GenAI to write code, speeding up the coding process and enabling them to produce more solutions in less time.
Task Automation
GenAI is also freeing up precious minutes and hours previously consumed by everyday tasks for various businesses, especially data entry, data management, and customer service.
Using GenAI, you can create a system that automatically recognizes patterns in the data types you put into specific fields. The system can then automatically input that information. For instance, it can analyze PDFs of insurance claims forms, identify claims data, and enter it into a database or another app.
Because GenAI can recognize patterns, it can also identify errors in data fields and even detect when information has been corrupted or changed. For example, before integrating manufacturing data into an ERP, you could have a GenAI identify outlying data points, such as those that are impossibly large, eliminate them from the dataset, or even correct them — automatically cleaning your data pre-integration.
One application of GenAI that has recently made a splash is custom chatbots. These use generative AI to answer customer questions and perform other human tasks, such as writing and research. In this way, a chatbot can answer questions about account balances, how to use products, insurance claims, and much more. You can even give employees chatbots to serve as virtual assistants, helping them do more in less time.
National Training Network, Inc. (NTN) recently used GenAI to tackle a sticky challenge: turning written math problems into speech, so visually impaired students could get the same questions as those without sight impediments. NTN worked with Centric Consulting to build a solution after their previous system failed to meet expectations.
Part of Centric’s solution involved using OpenAI to turn inputs (in this case, math problems) into speech that the system could read to students. By combining OpenAI and other technologies, Centric developed NTN’s MathKEYmatics platform into an effective tool that helps level the playing field for all students.
Creating automation with GenAI, whether in the classroom or workplace, saves valuable time while boosting accuracy. By reducing the risk of employee error and making processes faster, these solutions improve the quality of work and free up your employees to focus on higher-value tasks.
Personalization and Customization
The creative powers of GenAI have also made it an effective partner in personalizing and customizing user and customer experiences. For instance, a GenAI system can create marketing campaigns that target specific demographics or customers with unique buying behaviors. By inputting information about a customer’s needs, desires, and past actions, you give GenAI all it needs to start designing a solution custom-fit for that individual’s needs.
Similarly, a GenAI can help you design product and service solutions based on customer preferences, past behavior, or your organization’s desired outcomes. For instance, you can tell a GenAI model how much revenue you want to earn over a single quarter. Then, share the services in your portfolio, how much revenue each generates, and their respective overhead costs. The GenAI can then suggest a selection of services to help you reach your revenue goals.
Healthcare providers have also partnered with GenAI to improve patient outcomes. For instance, a generative AI system can analyze healthcare data, detect patterns, and recommend advice doctors should offer patients. Practitioners who aren’t fluent in a patient’s language can use GenAI to write notes and speak on their behalf when their second language skills fall short.
As a result, GenAI improves customer, patient, and user satisfaction while also making it easier for organizations to have helpful interactions with more people.
Data-Driven Decision-Making
Some of the most impressive generative AI productivity gains stem from its ability to streamline decision-making by studying data and surfacing insights. For example, in manufacturing, you can give a GenAI a large dataset containing data, such as the speed with which a process builds individual parts.
You can then ask the model which components require the most people-hours to produce. You can also ask the AI to predict the production time for future factory runs based on trends it identifies in the data. With this information in hand, you can design production schedules and schedule workers in ways that optimize efficiency.
Another industry example: The level of risk in the financial industry is particularly high, which may cause some investors to shy away from AI-powered tools. Would you trust a GenAI solution to help you make investments? In September 2024, QuantumStreet AI and Star Union Dai-ichi Life Insurance (SUD Life) announced they were banking on that.
They’re collaborating to develop a generative AI-powered investment analysis solution. Powered by IBM’s Watsonx, the system is designed to digest huge amounts of information and provide analysis that investors can use to make decisions. While the stakes are high, the risk of not being able to consider enough data before pulling the trigger on an investment may be compelling enough to draw investors to the two companies’ solutions.
Given the mountains of data companies have at their disposal — both in the public domain and from their own systems — having an AI-based system that improves the accuracy and speed of decisions can result in a significant competitive advantage.
Addressing Challenges and Ethical Considerations of Generative AI in the Workplace
As is the case with many technologies, you’ll want to keep certain ethical considerations top of mind as you decide when and how to enter the GenAI sphere:
- Employees may feel threatened by GenAI, especially if it can perform tasks they normally do. To assuage any fears about job displacement, you can ask employees how they’d like to use a GenAI solution to make their jobs easier.
- Data privacy is another issue because GenAI systems collect, analyze, and store data to generate outputs. You have to ensure your data processing and storage meet data privacy regulations such as HIPAA and GDPR.
- Ethical issues have arisen because some AI systems have discriminated against certain groups because they identify patterns rather than consider bigger-picture issues. For instance, AI-powered resume readers have shown bias because data scientists trained them on data showing the success of only certain demographics.
- Transparency is also key, particularly because you need to earn trust to secure stakeholder buy-in. Be open about the datasets your GenAI gets trained on, as well as any biases you may be concerned about. Also, you should openly share your entire roadmap for using a GenAI to ease concerns around people losing jobs to “robots.”
GenAI: Your Productivity Partner
Like many automation tools, generative AI improves the accuracy and quality of many repetitive tasks. But what makes it unique is its ability to analyze data, draw conclusions, make recommendations, and create. If these tasks are on your employees’ to-do lists, one or more GenAI systems may be the assistant they’ve been hoping for.
GenAI is poised to continue its ascent, especially as quantum computing and faster network solutions make it possible to process more data in less time. You may soon have access to GenAI-powered work buddies that perform diverse tasks, freeing up employees to hyperfocus on customer satisfaction.
While the potential of GenAI productivity gains is exciting, it’s important to consider the human implications of any implementation before moving forward. Let your staff dictate how they’ll use a solution, and constantly reiterate that it’s a tool to improve their productivity, not steal their jobs. By putting people first, you can inspire widespread adoption of GenAI and a culture that supports constant innovation and improvement.
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