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[So much debate and energy are being expended by financial leaders on AI’s trajectory and real-world applications, along with the potential risks and major benefits. Unfortunately, it has proven to be a difficult process for many financial firms to determine and implement definitive AI applications into their firms. A dizzying, ever-changing array of AI options and use cases have shown up in discussions across the full range of a firm’s operating environment and critical functions – data, workflows, sales/distribution, marketing, decision-making, business strategies, and client engagement.
One of the biggest challenges is learning how to best grapple with this rapidly accelerating technological environment. How do you strategically think about, discern, choose, and introduce AI into your firm? A well-defined strategy of action at minimum seems to be needed to guide the effort by providing some roadmap or pathway to clarity. The question is how do you develop a strategy for your firm to be able to efficiently navigate AI and other rapid technological shifts that will continue to be coming our way?
To help us answer that million-dollar question, we reached out to our long-standing innovation colleague Lynda Koster, co-Founder and Managing Partner of Growthential – a unique innovation-focused business and marketing growth consultancy, with financial services being a big focus. The firm has bundled many services into their AI Strategic Suite – a modular consulting service designed to help firms with strategic planning, risk mitigation, and change management by meeting them wherever they are in their AI journey. Their combined “strategy-first” and active experimentation approach to AI adoption is crucial to avoid the common pitfalls of previous technology waves which has often led to failed implementations and wasted resources.]
Hortz: Why was one of your company’s first actions in response to the launch of ChatGPT to immediately form an AI incubator and governance committee?
Koster: There were two big drivers along with one big reinforcement. First, having lived through previous technology booms (and hype cycles), we recognized immediately that the launch of ChatGPT marked a pivotal moment. In past waves, like the MarTech explosion, tools grew from 150 in 2011 to well over 15,000 today based on Scott Brinker’s MarTech landscape reporting. Especially early on, many organizations jumped into a “tool-first” reaction without a strategy, governance, or cross-functional alignment. Many times, I would receive calls from leaders under pressure along the lines of: “We bought this tool and need to launch in two weeks, but it’s not as easy as we thought it would be.” These were not failures of intent, but of approach. Quick, “tool-first” decisions often led to costly rip-and-replace cycles, longer integration timelines, and disappointing ROI. What those experiences taught me is that success requires starting with people, workflows, and governance; not with technology alone.
Second, I have also always worked at data-driven companies and in data-driven roles, so it was clear from the start what this level of open access to AI would mean. Unlike previous waves introduced through IT or business units, ChapGPT was released to the masses, followed by additional entrants like Bard, Claude, and Llama, before even their creators fully understood its behaviors (and still don’t). That kind of scale, speed, and uncertainty demanded a more intentional response.
That is why one of our first actions was to form an AI incubator and governance committee. We formed it early, not because clients were ready that day, but because we wanted to be prepared when they were. It allowed us to learn, experiment, develop emerging best practices responsibly, and establish guardrails for safe use…all with the goal of helping clients build readiness while avoiding the pitfalls of uncoordinated adoption.
The big reinforcement came when I listened to Sam Altman testify before the Senate Judiciary Subcommittee in May 2023, while traveling to an event I was speaking at. Those three hours of testimony further crystallized what was already clear: AI is more than a technical shift. It is a leadership challenge that touches culture, governance, and trust. Addressing these upfront is what will allow innovation to scale responsibly.
Hortz: For a mid-sized financial advisory firm with limited resources, what do you suggest are the single most important steps they should take on their AI journey?
Koster: For mid-size financial advisory firms with limited resources, the key is to start small but strategic. First, build AI literacy at both the leadership and team levels. Make sure people understand what AI is and, just as important, what it is not. And understand where the capabilities are today versus some of the hype in the market. That grounding keeps expectations realistic. This prepares you for the mindset needed as these capabilities evolve and for leadership to create the conditions needed for responsible exploration.
Next, put simple guardrails in place around usage, especially data handling and accountability, which can prevent missteps. Think of it like starting a new workout routine. If you dive straight into the heaviest weights without mastering form and safety, you risk burnout or injury. In AI, literacy is the form, guardrails are the safety gear, and pilots are those first manageable reps that build strength. Choose one or two focused pilots tied directly to business goals like simplifying onboarding materials or automating meeting notes. Define what success looks like and measure it. This way you are cutting through hype, staying grounded, and building sustainable momentum without overwhelming your people or resources.
And if you are further along in maturity and past the pilot stage, the priority becomes scaling what works, embedding governance more formally, and ensuring AI adoption is fully aligned to strategy rather than running in pockets of the business.
Hortz: How did you design your AI Strategic Suite to help financial professionals actually build and keep developing an AI plan that is right for their firm?
Koster: We started on ourselves. The first thing we did when ChatGPT launched was form our own AI incubator and governance committee. We did not want to simply talk about responsible adoption; we wanted to experience it, test it, and pressure-test the process inside our own business. Walk the walk, so to speak. That allowed us to see firsthand what worked, what broke, and what guardrails we needed to put in place before advising others.
From that experience, the AI Strategic Suite was born. It is designed the way we applied it to ourselves: start with literacy, strategy, measurable pilots, and workflows. Build small, but meaningful pilots. Put governance and safeguards in early so experimentation stays productive and aligned. And this is key – keep it evolving and actionable. We have made the Suite a living system so we can update as the tech and regulations shift, not a static, “one and done” plan.
And now, we have a growing alliance ecosystem, which is an extended bench of people and partners we have vetted and trust – from compliance and risk experts to technologists pushing the edges. It gives our clients a way to pilot, consider fast prototyping options, and eventually scale without hiring an army.
The result is a practical, grounded approach to AI that has been, and continues to be, tested in real life, and built to grow over time.
Hortz: Can you discuss how the AI consulting process and collected resources of tools and frameworks you offer are delivered and help guide firms through every step of their AI journey?
Koster: With or without AI, we always begin by meeting firms where they are. For AI specifically, every firm has a different starting point on the AI maturity curve. Some are just trying to get their arms around what AI even means for them, while others are already experimenting. So, the first step is listening: what are the pain points, what strategic priorities are on the table, and what problems are they trying to solve?
From there, we develop an actionable strategy (key word is ‘actionable’) and a tailored roadmap. For those interested, we have developed a centralized resources hub that is customized for each client engagement. Think of it as a “command center” – it pulls together tools, frameworks, and guidance in one place, so leaders are not chasing scattered resources or trying to piece things together.
The process itself is iterative. We guide firms depending on their AI maturity – step by step, starting with learning pathways if needed, then guardrails, then pilots, and scaling considerations. Each stage is designed to build confidence while staying aligned to strategy and safeguards.
And because no one firm has unlimited resources, we keep it practical: clear criteria for success, relevant frameworks, and a cadence that works for their capacity. The goal is not to overwhelm with complexity; it is to make the experience accessible and strategies actionable and measurable.
Hortz: How did you build your “Growth Alliance” of vetted, external subject matter and expertise to support your AI Strategic Suite? Why did you feel this effort was important?
Koster: It really started in practice, not theory. One of the early requests we got from a financial services firm was asking us to clone our AI policy for them. That raised two flags at once: first, how quickly regulations and policies were shifting – state by state, region by region, and globally. And second, how different each firm’s needs really were. It was obvious we could not take a one-size-fits-all approach.
That is where our Growthential Alliance came in. We knew we needed depth of expertise across very specific domains – whether that was compliance, cybersecurity, risk, or sector-specific regulations. Rather than diluting strategy with siloed hand-offs, we built these vetted partners into our methodology. They are not bolt-ons; they are part of how we deliver. And it is still evolving.
Why is this important? Because in this space, trust matters as much as innovation. We have seen too many providers rush to market with solutions that do not meet critical standards. That is not a risk we are willing to expose our clients to. By building this ecosystem, we ensure clients get access to the right expertise and solutions at the right time – depending on their needs, and the strategies and solutions we recommend can standup to both innovation and scrutiny.
Hortz: Can you share some specific examples of how you work with financial firms to further illustrate your AI journey support process and results?
Koster: We see financial firms at very different stages of AI adoption. Many mid-sized firms are still in the literacy, foundation-setting, or pilot stage. They are focused on building comfort and literacy before committing to larger-scale adoption. In reality, many are still finishing modernization programs, updating legacy systems, centralizing and cleaning data, improving its access and operationalization of that data. Without those foundations, AI at scale simply is not possible. As Hope Frank recently wrote in a recent Forbes article, “companies must finish their digital foundation before scaling AI”…a point we see validated every day.
That is where we begin: foundations, education, and safe, focused pilots. For example, we worked with a financial services firm to design and deliver an accredited webinar for advisors. It was not “AI for AI’s sake”. It was grounded in their day-to-day, showing what is possible, what to watch out for, and how to bring advisors into the journey responsibly. It ended up being their top-performing webinar, which showed us two things: there’s appetite, and a need for literacy.
Next, we are helping businesses across verticals to plan and initiate their next steps by running targeted pilots in areas like onboarding, solution evaluations, dual-control risk assessments, content optimization efforts, and go-to-market strategies – all while beginning to shape their broader strategies. Across all of these, the approach is consistent: start small, anchor initiatives in business strategy, measure outcomes, and scale what proves effective. That is how trust takes root and how adoption can move from cautious experiments to sustained impact.
At the other end of the spectrum, we have been “in it” ourselves for nearly three years. AI is now embedded across our workflows (where it makes sense) with measurements in place and we have built a proprietary platform with customized agent capabilities to support our internal efforts.
For instance, we designed what became our AI Strategic Suite by starting small and structured. Like our clients, we faced challenges – how to experiment safely, avoid wasted effort, and delver real business value. By applying a disciplined framework, we cut research and analysis time by over 50%, embedded AI into workflows without adding headcount, and reduced compliance risk through dual-security controls, governance, and human-in-the loop oversight. Those results gave us a tested Playbook we leverage and customize for our engagements.
Hortz: What are some of the top AI use cases you tend to work on with your clients?
Koster: For many firms, the first high-value use case is personalization at scale. Mid-sized financial firms often struggle to tailor reports, onboarding documents, or educational content without draining resources. Generic AI outputs usually miss the nuance clients expect. Using our internal agent model as the blueprint, we develop secure, modular solutions where personalization speed increased by 60% cutting prep time from days to hours. Brand consistency improved, eliminating variability that weakens trust. Risk exposure dropped thanks to safeguards aligned with ISO/IEC and regulatory best practices.
Last but not least, we have developed strategic partnerships and are in different stages of co-developing new products or service offerings that open up potential new revenue streams. These are mainly focused on strategic intelligence, governance/security, workflow enhancements, and professional development. Based on our initial work, we believe these will benefit financial firms and other sectors as well.
Hortz: Any other final words on your AI journey and experiences that you would like to share with financial professionals?
Koster: Do not get distracted by the hype and noise. Focus. Set the foundations, prioritize literacy, and build in space for learning. Move quickly but not recklessly. Get a true understanding of where these capabilities are today (it’s not all a push of a button), pilot carefully, measure what matters, and scale only when ready. This is how financial firms can build AI adoption they can trust and sustain.
That is the approach we have taken ourselves and what ultimately inspired our offering – a practical way to help firms navigate their AI journey with structure, confidence, and guardrails.
This article was originally published here and is republished on Wealthtender with permission.
About the Author
Bill Hortz
Founder Institute for Innovation Development
To make Wealthtender free for readers, we earn money from advertisers, including financial professionals and firms that pay to be featured. This creates a conflict of interest when we favor their promotion over others. Read our editorial policy and terms of service to learn more. Wealthtender is not a client of these financial services providers.
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