At Hearsay’s Fall Roundtable & Retreat, the topic of AI—and how firms are preparing for this next big wave—was top-of-mind throughout presentations, peer roundtables, and planning sessions. It also sparked lots of lively discussion and debate!
Readying organizations—and people—for AI
To kick off the event, CEO Mike Boese shared how financial services leaders are starting to build organizational readiness for AI—with the expectation that it will likely impact virtually every customer and employee experience in the future.
To date, several of Hearsay’s customers have launched pilots to dabble in AI—but for many, the charter has been to proceed with caution. Despite a shared excitement about improvements to the EQ and IQ of AI models and an eagerness to explore benefits, customers agree that it's important to develop a groundwork for organizational readiness. Therefore, firm leaders are focused on learning more about AI and testing different use cases in order to feel comfortable navigating the risks and rewards it presents before implementing a broad-based rollout.
Mike encouraged firms to start small and explore use cases with high potential to safely apply AI.
Specifically, he suggested:
- Optimizing top-of-funnel activities, such as recommending the very best content for marketers and advisors by using AI to analyze audience insights
- Building deeper, better relationships by empowering advisors to target and build trust with prospects and clients using AI-powered marketing tools
- Effectively and efficiently managing corporate and compliance risk with the help of AI-assisted workflows and review tools designed to optimize human resources
Prioritizing trust as it relates to AI applications
As our founder and executive chairperson, Clara Shih, reminded us: We must adopt AI in a trust-first way, especially in a regulated industry like financial services, where guardrails are more applicable than ever. With the right preparation and planning, policies and procedures will help manage AI’s strengths and risks while supporting high-value use cases
As an example, Blake Moyer, Technology Director of Digital Client Experience at Edward Jones, shared how his 100+-year-old firm is innovating and scaling in anticipation of AI by leaning into four key principles for prioritization:
- Start with business outcomes that align with your portfolio or firm strategy
- Ready your technology: Unlock data to make it actionable
- Ready your people: Identify the skills your folks need (ex: writing great prompts)
- Start small: Focus on MVPs (minimally viable products) and pilot programs, then scale
Effectively mixing oil and water: AI and compliance
The obvious risks associated with Generative AI include copyright ambiguity, data privacy, and conflict of interest. Perhaps more pertinent, though, is the hidden risk of hallucinations—which may not trigger lexicons and could result in employees distributing false/misleading information—absent robust controls.
To mitigate these risks, presenters Lisa Robinson of Oyster Consulting and Hearsay’s Senior Product Manager Andrew Kugler reminded us that AI should be treated like any other technology.
The duo recommended firms focus on:
- Establishing policies and procedures that cover regular review of activity. How that review is evidenced is imperative for staying compliant in a dynamic regulatory environment.
- Providing ongoing training. Employees must be continually trained on how to mitigate risks, and access to AI must be restricted if necessary.
- Continually evaluating vendors to ensure alignment with ongoing regulations and your firm’s goals.
Because AI is advancing faster than any other technology, the dual efforts to train employees and evaluate vendors will help firms keep pace.
With the right guardrails in place, the practical uses of AI in compliance can bloom. Risk identification can be enhanced with smart lexicons that help identify sentiment—for example, in a promissory statement. It can also drastically reduce review time for a one-hour-long presentation by scouring images, audio, and video files and applying machine learning-powered risk scoring. When it comes to publishing, using AI to offer recommended content that’s already compliant can reduce the impact of writer’s block and speed time to publish—particularly for more novice users.
Finding authenticity in an AI world
Hearsay’s Sr. Director of Value Consulting, Tim Rickards, reminded us that in a content-saturated world, authentic communication is what truly stands out. Authenticity builds trust, and trust trumps everything—it’s the foundation of customer loyalty. It’s also no surprise that authenticity and value in our content starts with us!
While AI may promise customization at scale, it works best when it amplifies—rather than replaces—our abilities. “We come up with the questions for AI. We apply our judgment. We curate and create the content,” says Tim. He reminded us that behind Gen AI are prediction machines that we must guide to get truly relevant outputs. One of the biggest benefits is time saved researching; however, the time we as humans spend reviewing, curating, editing, judging, and making decisions is equally important.
Accelerating your social selling program
Our Head of Digital Transformation, Amanda Peitz, shared three key factors that help accelerate the effectiveness and time to value of your social media and texting programs:
- Setting multi-level, measurable goals at both the program and user level. While many program owners have goals like “Increase platform adoption to 80%,” they may be less familiar with setting user goals, such as “Engage with 10 direct first contacts by liking their published posts.” Both types of goals are equally important.
- Selecting and enabling the right platform(s). This means identifying where prospective clients are most active and investing efforts to target them through tailored content that also reflects the personal and corporate brands and deploying a channel-specific training strategy for advisors and agents.
- Measuring and analyzing behavioral data and tying it to business outcomes. This is done by understanding which behaviors drive user interactions (user maturity model), quantifying the value of interactions associated with published posts (earned media value), and using both frameworks to correlate social and texting behaviors with business outcomes.
Amanda spotlighted case studies featuring each capability and explained how customers can request a monthly report that provides individual user maturity scores and leaderboards. This data helps firms build a solid foundation for social selling acceleration and success.
We loved collaborating (and shucking oysters) with our awesome customers, and we can’t wait to do it again next spring! Stay tuned as we share details on our annual Hearsay Summit, happening April 15-17 in the Big Apple!