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Insights from PwC's Solver Series: Banking and Capital Markets Roundtable
Hosted at Dreamforce 2023
Generative AI is taking the world by storm. But with all the buzz surrounding the tech and its impact on business, how can companies break through the noise and approach AI responsibly, especially in the highly regulated financial services industry? These questions formed the basis of a lively roundtable discussion at the recently concluded Dreamforce 2023, where PwC shared insights into how companies can adopt generative AI confidently, ethically and responsibly.
After a decade of progress with artificial intelligence, we are at an inflection point. As Salesforce CEO Marc Benioff said, “This AI wave is going to be the biggest that anyone has ever seen.”
Executives agree that AI holds immense potential. According to PwC’s Global Artificial Intelligence Study: Sizing the prize, AI could contribute up to $15.7 trillion to the global economy by the end of the decade. Predictive AI capabilities have already been widely adopted within the market, with generative AI now seeing huge growth and interest.
In fact, PwC US is investing $1 billion over the next three years to expand and scale our AI offerings, helping companies reshape the workforce and become leaders in the responsible use of AI.
So how can financial services companies adopt generative AI and leverage its power for growth and success?
Our roundtable discussion revealed a number of key insights, including:
Generative AI use cases go beyond the hype
New technologies typically have a hype cycle in which companies come to grips with the promise of the technology and its actual use cases and adoption within the business. Even though it's still early days for generative AI, some common themes for adoption are emerging. These include improving customer satisfaction, managing risk and compliance, increasing operational effectiveness, unlocking innovation and coming to grips with changes in the market.
Companies share common steps toward generative AI adoption
Financial services companies are in varying stages of generative AI adoption, but all companies share five common steps, namely:
- Step 1: Establishing responsible AI security policies and a secure environment
- Step 2: Defining an AI strategy to prioritize use cases
- Step 3: Building initial use cases, which commonly include a private ChatGPT application, customer service and sales solutions, and a software development lifecycle solution
- Step 4: Scaling use cases by building AI into workflows and applications
- Step 5: Refining AI governance, security and responsible AI
Data quality is the greatest concern with generative AI adoption
We asked audience members via a quick poll what they believed to be their biggest hurdle in adopting generative AI. Top of the list was data quality: getting the right data into Salesforce and building a strong data foundation for the future. Other challenges cited include regulatory, compliance, governance and defining the business case.
Generative AI helps with the ‘why’ in data
To illustrate the emerging Salesforce use cases of generative AI in financial services, we used some prompts that aimed to make sense of customer data. This highlighted one of the most valuable abilities of generative AI: to reveal the potential reasons why a customer took a specific action. For example, if a customer has made an unusually large money transfer, generative AI could draw on multiple data sources to provide the reasons behind the transaction, such as paying off debt, taking advantage of an investment opportunity or making a work-related transfer.
What is the human impact of AI?
AI has brought on new challenges for organizations, such as the need for entire workforces to be upskilled, made comfortable with the concepts of AI and agreeable to its use of in everyday life. It has also surfaced fears in employers and employees about the need for continuous upskilling in order to keep up with the pace of change. This requires work at an enterprise level to set frameworks, governance and controls. However, the PwC speakers at the roundtable reminded the audience that AI is not a brand new concept and that it’s existed for years. It’s the recent focus on generative AI specifically that has brought the technology into the mainstream and made it a hot topic of conversation. PwC’s recent article on ‘6 generative AI business myths’ debunks these myths in more detail and shares perspectives on how to deploy generative AI quickly and securely.
Starting your generative AI journey with small steps and micro-learning
An effective approach to making generative AI manageable starts with identifying what can easily and safely be done in your organization. Start with basic, small use cases that focus on high-impact workflows, such as fact-finding, article retrieval and call note summaries. These are simple, safe ways to get started with generative AI within Salesforce. These small steps help demystify misconceptions and increase user comfort levels. The concept of micro-learning is also key in the early stages of onboarding with generative AI. This involves breaking down the curriculum into bite-sized parts that leverage video and other tools to make learning manageable and enjoyable for users.
What’s next?
Reach out to us today to learn how PwC is unlocking the innovation and growth potential of generative AI with Salesforce in the financial services sector.
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