Session presenters shared real-world case studies and success stories, uncovered the latest AI-powered tools and techniques, and provided actionable insights to empower attendees to harness the potential of AI in marketing initiatives. The webinar’s presenters were:
Keara M. Piekanski, director of marketing at Oakmont Capital Services and chair of the ELFA’s communications committee
Chelsea Jensen, senior employee engagement specialist at Sasser Family Companies
Kyle Mallinger, senior vice president of marketing at Financial Partners Group
Kristi Schon, chief marketing officer at Channel
Joseph Vu, senior vice president of marketing at QuickFi
More than 250 industry professionals registered for the Sept. 28 event, which kicked off with an interactive poll about attendees’ usage of AI tools. The top response revealed attendees use various AI tools daily, followed by the use of one or two tools to accomplish weekly tasks. The webinar, designed for all levels of familiarity with AI, included the following highlights:
What is AI? Generative AI is a model or algorithm that creates new output or content from data it is trained on. It is distinguished by three characteristics: It provides generalized rather than specialized use cases; it has the ability to generate novel human-like output rather than merely describing or interpreting information; and it has approachable interfaces that help understand and respond with natural language, image, audio and video Iterative AI’s ability to generate new content that is largely indistinguishable from human creative output and break down communication barriers between humans and machines reflects a major advancement with potentially large economic impacts.
Marketing leads adoption of AI. Over the last decade, marketing functions have been implementing the precursors that allow for widespread organizational use of AI. Marketing’s core activities, regulation and natural gravitation toward direct customer interactions are uniquely well suited to benefit from AI, according to the webinar presents. Having both the digital infrastructure and a direct connection to customers enables AI’s greatest use case in marketing and financial services.
Integrated machine learning. One of the most common AI applications used by marketers, machine learning can create large efficiency gains and inspire new tactics for go-to-market efforts and lead generation. However, it’s not a pre-built, standalone platform that is just installed; it’s constantly growing and evolving. Therefore, one of the biggest challenges is how people enable machine learning to learn and teaching the model what to look at and what to understand, creating an advanced CRM platform that will have elements of AI built in. Ultimately, a company’s technology, teams and strategy will determine what’s appropriate for how a group leverages this tool.
Potential pitfalls. AI is far from perfect, and there are pitfalls to be aware of and steps to mitigate when creating AI-generated content. Factual fallacies occur with machine learning since it’s programmed with human input, so it’s necessary to cross check output with other sources. It’s also not SEO-friendly, so adjustments must be made for tone or slant, keywords and optimizing for web use. For privacy and data protection, ensure the AI tool is reputable and not malware, and never input proprietary information since it can be shared with competitors and other external users. Machine learning bias exists, which can show a preference for a particular demographic. Finally, AI generates homogenous content so human input is still needed to provide nuance and review.
Legislative response. There are currently no comprehensive federal regulations in place for AI. The White House has issued a blueprint for an AI Bill of Rights, a list of proposed principles to guide the design and use of AI technology that protects the public and would need to be enacted by Congress. At the state level, nearly 90 pieces of AI legislation were either enacted or proposed during the 2023 legislative session. Ten states included AI regulation as part of wider consumer privacy laws, and more states have proposed similar bills. The following map illustrates AI legislative action taken in the U.S. in 2023.
In addition to these highlights, the committee provided the following summary checklist to help guide adoption of AI in organizations:
Utilize AI in a way that’s relevant and impactful for day-to-day duties.
Don’t be afraid to get started/try new tools/ask questions/dig in deeper. Tools are free or low cost.
Be cognizant of “dangers” and mitigate them, but don’t freeze in fear.
Prop up talented team members by encouraging them to enhance output through AI.
Follow the legislation, as it may impact certain states and/or the overall equipment finance and marketing industries.
A recording of the Sept. 28 webinar, the slide deck and a resource guide of online articles and regulations on AI are available here.
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