**The Future of Working with Generative AI**
According to Don Schuerman, the chief technology officer at Pegasystems, generative AI tools like ChatGPT will become a normal part of working life in the next five years. Pegasystems is a US-based company that develops software for large organizations to manage and automate their business processes. Schuerman compares utilizing generative AI to knowing how to write an Excel formula. However, the potential of generative AI goes beyond just automating tasks; it can also help businesses achieve their goals.
The concept of the Autonomous Enterprise centers around companies being able to set business targets, and then utilizing AI-enabled processes to learn how to reach those goals. While companies are intrigued by this concept, they are taking their time to deploy generative AI, especially in regulated industries such as banking, healthcare, and insurance. These industries want to thoroughly understand the potential risks involved and ensure compliance with regulations.
One concern that companies have with using large language models like ChatGPT is the risk of exposing private company data. There is also the issue of generative AI models potentially producing incorrect or misleading information. Schuerman believes these problems can be solved or mitigated. One potential solution is Retrieval Augmented Generation (RAG), where a query is fed into the software along with the relevant data needed to answer the query. If the AI system cannot find the answer, it will respond with “I don’t know” to minimize the risk of generating false information.
Pegasystems has developed an AI interface that can synthesize answers from different documents, making it easier for users to access information. This approach is of particular interest to insurers, who want to provide their claims managers with best practice information to solve problems related to claims. While generative AI will not replace the need for individuals with deep business knowledge, it can help them work faster. For example, it can be used to automatically generate test data or train AI chatbots, thus speeding up software development.
In terms of regulation, Schuerman emphasizes the importance of including AI experts who understand the impact of regulatory decisions on consumers, employees, and businesses. Pegasystems is not part of the UK government’s exclusive international AI safety summit, but Schuerman believes it is crucial to have knowledgeable individuals involved in the regulatory discussions.
Pegasystems’ vision for the future, called the Autonomous Enterprise, involves enabling organizations to set business goals that guide their processes. These goals can be continuously optimized and improved to meet business objectives. For instance, a bank could aim to reduce the time spent on credit card disputes without paying unnecessary compensation. The software would analyze historical trends and escalate cases that could lead to delays or unnecessary payouts. Businesses would have the flexibility to adjust their goals as needed.
Automating processes takes time, starting with creating structured processes for employees to follow and then automating the tasks. Once tasks are automated, businesses can collect data on their transactions and use AI and machine learning to make predictions and identify potential issues. Each step in this process can generate a return on investment.
**Editor’s Notes**
Generative AI tools like ChatGPT have the potential to revolutionize the way we work, but there are still challenges to overcome. Concerns about data security and the production of incorrect information need to be addressed. It is essential for decision-makers and regulators to have a deep understanding of AI technologies to ensure effective regulations. Pegasystems’ approach to the future, the Autonomous Enterprise, holds promise for businesses looking to optimize processes and achieve their goals. However, implementing these changes will require time and careful planning.
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