The artificial intelligence (AI) space was already evolving quickly but, since the emergence of high-powered Generative AI models, that evolution has accelerated massively and we’re seeing a constant flow of new solutions and use cases. Generative AI has swiftly emerged as a groundbreaking technology with incredible potential.
Unlike traditional AI, which analyzes and learns from existing data, generative AI is capable of actually creating new content, from crafting human-like text to generating images or music. This significant shift in AI capabilities is transforming industries and businesses are eagerly exploring ways to leverage its human-like skill sets.
In fact, despite its newness, it’s starting to feel like if you’re not integrating GenAI into your tools and processes, you’re quickly falling behind. Now, that may well be an exaggeration stemming from the influx of GenAI innovations since OpenAI launched ChatGPT half a year ago. But, even as the model is constantly being improved, there’s no question it’s become a priority across industries. It almost feels like ChatGPT has re-written the news cycle to feature Generative AI.
While that’s clearly not reality, what is real is the dominance of GenAI is business tech headlines. Among the most recent company’s to get on the bandwagon is Pegasystems, which has announced a suite of twenty new generative AI-powered boosters, aptly named Pega GenAI, which will be integrated into its low-code AI-powered decisioning and workflow automation platform by Q3 of this year.
The introduction of Pega GenAI is a strategic move to harness the existing and emerging capabilities of generative AI. The technology has been making waves in the tech world, drawing interest from diverse verticals and business functions.
As businesses continue to grapple with the challenges of digital transformation, the demand for AI-infused solutions has surged. The promise of GenAI lies in its ability to create new content, make decisions, and automate workflows – the latter two are areas where Pega has extensive experience – and is not adding the former with its Generative AI integration.
For instance, consider a bank aiming to automate its loan processing operations. Traditionally, the bank would need to develop dozens of workflows from scratch – a time-consuming and complex process. With Pega GenAI, the bank simply needs to inform Pega that it’s creating a “loan processing application.” Pega GenAI takes it from there and leverages Generative AI models, like OpenAI’s ChatGPT, to generate the related workflows, data models, user interfaces, sample data, and more. This level of automation and intelligence can revolutionize operational efficiency across industries, as it drastically reduces development time and enhances the quality of outcomes.
Pega GenAI is Packed with Features
With 20 GenAI-powered features, Pega is touting Pega GenAI as a game-changer across various sectors. Here are a few ways Pega GenAI boosters will enhance functionalities in the Pega Infinity '23 platform:
- Faster low-code application development – AI-prompted workflows, AI-generated personas, automatic data modeling, back-end integration assistance, and sample data generation will transform the pace and quality of application development.
- Enhanced customer engagement – The Customer Decision Hub will see improved treatment creation assistance, higher impact action recommendations, explainable AI analytics, and population targeting and validation, enabling businesses to optimize engagement policies and better understand AI decisions. To many, the ability to understand AI decision-making is a key to appropriate implementation of AI and a major factor in its trustworthiness.
- Improved customer service – Features like automatic interaction summaries, accelerated chatbot training, a customer interaction simulator, and advanced chatbot responses will augment customer interaction, reduce manual work for customer service agents, and streamline chatbot deployment.
- Increased productivity – Pega Sales Automation and Robot Studio will feature tools like an email reply generator, a meeting summary generator, script generation, and test data generation, enhancing productivity and streamlining bot creation and debugging.
- Enhanced knowledge management – Pega Knowledge will offer semantic search and generation of new answers, facilitating natural language inquiries and the creation of succinct articles. This feature, alongside the ability to generate reports via Pega GenAI, offers more accessible operational insights.
Pega GenAI is built on a new API abstraction layer called Connect Generative AI. This layer promotes a plug-and-play architecture, enabling organizations to gain immediate value from generative AI with low-code development of AI prompts. Importantly, Connect Generative AI ensures data protection by automatically replacing PII data with placeholders in prompts, helping organizations enforce their data protection policies and advancing secure use of public and private models.
This capability to rapidly create and modify applications using generative AI represents a paradigm shift in the development process. Pega's model-driven architecture enables low-code developers to easily configure and adjust these AI-suggested starting points, delivering completed applications with unprecedented speed and efficiency.
The Generative AI-powered boosters in Pega Infinity '23 enable low-code developers to infuse generative AI functionality into decision-making and workflow automation. The “AI choice” architecture Pega provides allows it and its clients to continuously innovate new secure solutions. Connectors will initially be offered to OpenAI's API and Microsoft Azure's OpenAI APIs and will be supplemented by additional downloadable connectors to other providers on the Pega Marketplace.
As many have opined, there are risks with such new technologies, including many unknown risks when it comes to AI-generated content. Pega's approach to generative AI emphasizes the responsible and governed deployment of AI models. It includes auditing, rules-based governance, and workflow-managed human approval to advance safety, security, and reliability. All AI-generated text can be reviewed, edited, and approved by authorized staff to mitigate the risk of inaccurate or biased text being exposed to customers.
Edited by Erik Linask