In this episode, Brian and Andrew sit down with Jase Bumgardner, a 25-year partner at The Link Group, a healthcare-focused market research consultancy. Jase leads complex, multi-year research work streams in neuroscience and new product planning, most notably alongside Eli Lilly, following products from early concept all the way through FDA approval and launch.

Jase brings a grounded, refreshingly calm perspective to a conversation the podcast usually approaches with a bit more urgency. Where Brian and Andrew often find themselves in the AI doom spiral, Jase comes in as a self-described pragmatist. He estimates AI has changed roughly 10 to 15 percent of what his team actually does day to day, and he sees it primarily as amplification, not replacement. The real disruption, in his view, is still mostly theoretical for firms doing elite, high-stakes consultative research.

The conversation covers how The Link Group made AI a formal priority years ago through a structured task force, a five-year strategic plan, and ongoing sentiment checks to see if it's actually moving the needle with clients. Jase also pushes back thoughtfully on the rush to adopt, citing data showing only 13 percent of brand-side clients are satisfied with generative AI results, and warns against what he calls the "great de-skilling," where reflexively outsourcing thinking to AI erodes the very capabilities that make great researchers irreplaceable.

Key Takeaways:

• How The Link Group built a deliberate, mission-aligned AI strategy rather than chasing every new tool

• Why the "any benefit" mindset around AI adoption is a problem, and how to think about net benefit instead

• The risk of de-skilling as reading, writing, and independent thinking get offloaded to AI tools

• Why market research is still fundamentally a talent and relationship game, and why that is not changing anytime soon

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In this episode of Signal and Noise, Brian and Andrew sit down with Erin Sowell, owner and principal consultant at Thoughtful Research. Erin brings a background that is genuinely uncommon in the insights world, starting in environmental science and entrepreneurship before discovering market research through the product development process and going on to earn her master's degree from the University of Georgia's highly regarded MMR program, where she now serves on the advisory board.

The conversation digs into what it actually looks like to run a small, independent research consultancy built around integrated insights, bringing together qual, quant, and existing client data to answer business questions rather than just execute studies. Erin walks through a real project where a B2B client had a product that customers asked for and then refused to buy, and how a phased qual-to-quant approach helped uncover that the problem was not the product but the positioning and targeting strategy around it.

Brian and Andrew also explore one of the more underappreciated challenges in the industry: working with clients who have never done primary research before. Erin talks candidly about what it means to not just sell a study but to introduce an organization to research itself, the white-glove education involved, the sticker price shock, and why getting that first impression right matters so much for the long-term relationship a client develops with insights as a function.

Key Takeaways:

• How Erin built Thoughtful Research around integrated insights and a consultative, business-first approach rather than a methodology-first one

• The unique challenge and opportunity of working with clients who are brand new to primary research

• How Erin is using AI for qualitative analysis and building toward always-on forecasting and leading indicator capabilities

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In this episode of Signal and Noise, Brian and Andrew ditch the agenda and go full rant mode, recording from Andrew's hotel in Atlanta with no guest, no script, and no filter.

The topic is AI anxiety. Not the doom spiral variety, but the very real, day-to-day frustration of trying to stay current with a technology that moves faster than any organization can evaluate, approve, or implement. Andrew frames it as trying to build a robot underwater with one arm tied behind his back, in a wave pool, while the water keeps changing.

The conversation gets honest about what this looks like in practice, from juggling a growing personal stack of AI tools to navigating the very different constraints that come with using AI inside a company holding PII, client data, and SOC 2 compliance obligations. They land on a practical and surprisingly calming framework: stop chasing the best model and start building your processes in a model-agnostic way so your work survives the next wave of change regardless of which tool wins.

The episode ends with both hosts arriving at genuine excitement rather than dread, and an open invitation for listeners navigating the same thing to come on the show and talk through it.

Key Takeaways:

• Why AI anxiety is a real and shared experience for market research professionals right now, and why the pace of model releases makes organizational adoption feel nearly impossible to time correctly

• The case for being model agnostic and building AI workflows that do not depend on any single tool or provider, so your work survives the next wave of change

• Why the Anthropic report on AI exposure by industry means market research professionals should be excited, not threatened

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