From Potential to Practice: How to Drive Enterprise Transformation with Generative AI Platforms

4 minute read

Explore the key takeaways from our highly attended webinar, What’s Next in Generative AI for the Enterprise.

Generative AI platforms are poised to help enterprises reach unprecedented levels of operational efficiency and service excellence, but most organizations are still left wondering how to get there.

Last month, we hosted our webinar, What's Next in Generative AI for the Enterprise, to explore this very question. More than 200 enthusiastic participants from around the world tuned in live to hear from our prominent guest speaker, Forrester Vice President and Principal Analyst Craig Le Clair, and Amelia's Chief Product Officer Brandon Nott.

Given the continued discussion – and confusion – around Generative AI and its business value, the primary objective of this webinar was to demystify this technology and its place in the enterprise setting. To do so, our speakers delved into the practical applications and limitations of Generative AI and Large Language Models, as well as what it takes for businesses to get started with Generative AI today.

Practical Applications and Limitations of Large Language Models

In his insightful presentation, Craig Le Clair shed light on the roles and risks of Large Language Models (LLMs) in the enterprise landscape. As LLMs have grown increasingly popular, incidents involving this technology – including bias, misinformation and surveillance – have also spiked. The recent rise in incidents reflects people’s over-trust in LLMs, especially as their outputs have become more impressive and realistic.

The business value of LLMs is not negated by their limitations; however, it is critical that they are implemented correctly. As Le Clair pointed out during the webinar, for LLMs to truly add value to a business, they must be integrated into existing processes. This also means that LLMs should not be deployed as standalone solutions, but rather as tools that enhance current operations and job functions.

Looking ahead to the future of automation, Le Clair spoke about the concept of "Shared Authority,” in which both humans and machines partake in decision-making processes. He proposed viewing LLMs as micro-apps that can be incorporated into enterprise processes at critical junctures to boost both efficiency and the user experience. However, to ensure the safety and effectiveness of these language models, their inputs and outputs must be monitored and shaped by humans.

For organizations that are ready to take the leap with this technology, Le Clair presented three main avenues for businesses to utilize LLMs: businesses can leverage an open-source LLM and run it from behind their own firewall, engage with cloud-based API services to allow for direct interaction with models or use LLMs via vendor-provided software and applications, such as Amelia.

Embracing Generative AI Platforms for Business: Amelia’s Vision and Role

The increased interest in Generative AI has also brought more attention to the role of Cognitive AI, with many people asking how these two technologies compare. Brandon Nott’s presentation unpacked why the conversation around these two technologies should not be framed as “either / or,” and instead should center around how these technologies work together.

Nott used the concept of synergy to illustrate how the successful implementation of both Generative AI and Cognitive AI is critical for businesses to excel in this new era of automation. To further expand on this point, Nott outlined three areas where Generative AI plus Cognitive AI will drive the most business value: including building, experiencing and optimizing with AI.

When it comes to building with AI, Nott highlighted how Generative AI significantly reduces the time required to create automation flows. For example, developers can ask Generative AI to provide additional types of utterances to expand on initial ideas, enabling businesses to benefit from the power of Generative AI in a safe way, as developers can choose to accept or reject the generated outputs.

Generative AI plus Cognitive AI also helps drive superior user experiences when leveraged within a Conversational AI platform. For instance, if a user asks a question where the intent is unclear, an IVA can leverage the company’s corpus of FAQ information to generate a response that helps the user get closer to their resolution. The IVA can also tell the user where they found the information, demonstrating transparency and increasing user trust.

Lastly, Nott discussed how AI helps businesses improve their implementations over time. As we have stated before, AI is not something businesses should set and forget. Instead, Generative AI can help organizations realize areas they missed during their initial implementation by suggesting ways to improve, and the recommendations can then be codified into the platform for future use.

The combined power of Generative AI and Cognitive AI platforms therefore accelerates automation development, drives better user experiences and enables continuous improvement of implemented solutions, making this a winning combination for enterprises.

Audience Questions About the New Age of AI Platforms

Our audience submitted dozens of questions during the webinar, many of which were addressed by our speakers. Here is a glimpse at what foreword-thinking business leaders are asking about:

  • Question #1: How should companies be thinking about their own Intellectual Property, Personally Identifiable Information and customer info being pushed through an LLM? What is the landscape today and what does the future look like?
  • Question #2: How do I handle a C-Suite that sees Generative AI and is putting pressure to benefit from Generative, but not putting the investments behind it to do so responsibly?
  • Question #3: What happens to people who don’t step into using AI?

For answers to these questions and more, be sure to watch our on-demand replay!

We hope our webinar shed light on the benefits, pitfalls and vast potential of Generative AI platforms in enterprise settings. We extend our gratitude to our audience for their active participation, to Craig Le Clair for his expert commentary on Large Language Models and to Brandon Nott for illuminating Amelia's leading-edge work in this area.

As the interest in AI platforms continues to surge, we are excited to keep pushing the boundaries and leading the conversation. Keep an eye on our Media Center and social channels for the unveiling of the next version of Amelia!

Gartner® Explores Generative AI Plus Conversational AI

Technological research and consulting firm Gartner recently published a report that delves into the addition of Generative AI capabilities into Conversational AI solutions, and the resulting impact on user experiences.

Click here to access your complimentary copy of "Gartner Emerging Tech: Use Generative AI to Transform Conversational AI Solutions."

Access the Report