This is the eighth in a series of blogs on the “AI is here.” podcasts. Each blog in the series will highlight the insights from a specific industry leader as they describe how their organization is deriving significant value from AI today.
In this edition of the “AI is here.” podcast, Dan Faggella, Founder and CEO, of market research and publishing company Emerj, and Marshall Choy, SVP of Product with SambaNova, discuss where AI is being successfully deployed, what the organizations that are successfully deploying AI look like, and how they view new technology adoption.
According to Choy, AI is finally here. Deployments of AI have now reached a level of maturity and organizational readiness where there are meaningful deployments at the organizational level in forward facing organizations.
Just a few years ago, this was not the case. Only the hyperscalers had the budgets, technical resources, and the data science capabilities to do so. However there are now meaningful deployments that have gone beyond the pilot stage and are in production.
There are a significant number of organizations that have moved from simple experiments to foundational deployments. While not prevalent across all organizations, those that are innovating and leading have a recognition of the need for an AI foundation.
The challenges that many organizations are facing is that they implemented AI programs without a comprehensive strategic vision in place. Instead they launched a number of small scale AI experiments to try to understand where they could get value from the technology. As a result they have developed a large number of small, task specific models. In some cases, large organizations may have thousands of small models in use. This makes managing and maintaining all of those models extremely costly and complex. Plus, it becomes difficult to meet compliance requirements as the data set upon which a given model was trained could be unknown. Now these organizations have to go back and start over with a foundation model approach.
Organizations where AI is delivering real business value are those that start with architectural and data maturity, combined with a coherent strategy across the enterprise. It begins with C-level alignment and flows through the organization, across the data scientists, all the way down to the line of business teams. This allows them to have a thought out approach to what they want to accomplish and how to achieve it, while avoiding endless circles of discovery through experimentation.
Choy observed that forward-looking enterprise organizations are now utilizing Large Language Models (LLMs). LLMs are appearing across a broad range of industries with the common theme being that they are either speech, text, or document heavy industries. The industries at the forefront include banking and financial services.
LLMs understand language data with human level accuracy and can generate new content. The leaders in this area are innovating with LLMs to power applications and use cases across the organization, from the front end call center, the back end risk and compliance workloads, and everything in between.
The key takeaway is that there is a shift in thinking at leading organizations. There is an understanding that what is needed is a foundation model to set the backbone of the organization.
That is why there is a shift to large language models as the foundation model for the workloads of today and those of the future. It is being driven at an executive level with a strategic mindset around AI deployments. Beyond that, it needs to start with a core and native approach across the organization. It needs to be inclusive of multiple functional aspects across the organization, including CxO level ownership, formal AI centers of excellence and governance committees, along with all the technical staff who are doing much of the difficult and painstaking work to make this happen in real time.
Just as with other big technology shifts, organizations are no longer seeing AI as simply a bolt on activity. It is an organization-wide initiative, often so much that it shows up in annual report filings, and is reflected upon the assignments of employees from the executive level all the way down.
Faggella agreed that those who are doing well with AI are those with a high-level executive mandate and have what he called AI fluency. He commented that a C-suite with a coherent picture of what AI can and cannot do along with a long term plan to implement it is rare and asked about how those with this level of AI fluency arrived at that point.
Choy pointed out that there are two basic ways to think about new technology implementations. There is the more traditional mindset which looks at how the technology can save in terms of time, money, or staffing resources. It is a very tactical, short term mindset. For those with that type of mindset, AI may not make a lot of sense.
Then there are those with a more strategic view and are investing in AI with conviction. They understand that AI has the power to transform their organization, but to do so it must be applied broadly. AI cannot transform the enterprise if it is only applied at the departmental level. They are looking at how AI is going to enable them to deliver the next generation of products and services, and how AI is going to help them improve their customer experience and customer retention. They are taking a more strategic view and looking at measurements that are tied to bottom line revenue generation.
Examples of this include traditional enterprises like banking, which hasn’t changed much in 200 years, and is about to change completely. There is a focus on how to improve the customer experience, how to more uniquely engage with customers to the point where many of these companies that have “bank” in their names may one day drop the word bank from their name, because very soon Banking and Financial Services may only be one of many supporting services they provide to their customers. They are in a true transformation. There are many examples of this from the internet days where many companies changed from their core competency and install base to something very different.
Finally, Choy spoke about something that is evolving very quickly in Europe and Asia and other countries as well, which is the adoption of AI being coordinated at a national scale, rather than a corporate one. That requires a whole different level of engagement and partnership with vendors and partners to do it right. That is something that SambaNova has been very proud to be a part of and jump start.
AI is here. Discover how you can fundamentally transform what is possible for your organization with the power of AI in weeks, not years. Powered by the industry’s most powerful, full stack deep learning platform, SambaNova is the industry leader for GPT and large language models, delivering the highest accuracy and performance, while dramatically reducing the need for significant investment in infrastructure, personnel, and other resources.