Catharine Montgomery Of Better Together Agency On How Artificial Intelligence Can Solve Business Problems
An Interview With Chad Silverstein
Rather than replacing humans, AI works best when paired with human creativity and judgment. These collaborative teams combine AI’s processing power with human empathy and strategic thinking. For a reproductive rights campaign, we developed a workflow where AI agents handled research, content drafting, and performance analytics, while our human team focused on storytelling, relationship building, and strategic direction. This human-agent collaboration allowed us to produce three times the content with the same team size, reaching more communities with personalized messaging. The AI handled data-heavy tasks while our team provided the emotional intelligence and cultural context essential for sensitive topics.
In today’s tech-driven world, artificial intelligence has become a key enabler of business success. But the question remains — how can businesses effectively harness AI to address their unique challenges while staying true to ethical principles? To explore this topic further, we are interviewing Catharine Montgomery.
Catharine Montgomery is the Founder and CEO of Better Together Agency, a purpose-driven communications agency addressing critical societal challenges through innovative strategies and messaging. With more than 15 years of experience in public relations, she specializes in education, environmental, and social justice issues while pioneering efforts to uncover and mitigate biases in generative AI. Catharine’s thought leadership empowers organizations to integrate ethical AI practices, driving technological innovation that serves and uplifts diverse communities.
Thank you so much for joining us in this interview series. Before we dive into our discussion, our readers would love to “get to know you” a bit better. Can you share with us the backstory about what brought you to your specific career path in AI?
My journey to working with AI wasn’t planned but evolved naturally from my communications background and commitment to equity. After founding Better Together Agency, I noticed how quickly AI tools were transforming the communications landscape, creating both opportunities and challenges for our clients.
The turning point came during a client project where we were using an AI tool to analyze audience sentiment. The tool consistently misinterpreted cultural references and expressions common in Black communities, leading to flawed analysis. This wasn’t just a technical glitch; it represented a fundamental problem that could impact how organizations understand and serve diverse audiences.
Rather than simply avoiding these tools, I saw an opportunity to help shape them. I began researching AI biases, connecting with experts in the field, and exploring how communications professionals could contribute to more inclusive AI development. This eventually led to our agency’s focus on ethical AI implementation and our research initiatives like the Biases in Generative AI Survey, which has become a cornerstone of our work in this space.
Can you share the most interesting story that happened to you since you started working with artificial intelligence?
One of the most eye-opening experiences happened during a workshop I conducted for a tech company on inclusive AI development. We demonstrated bias in various AI systems when a senior executive interrupted with skepticism, saying he’d never seen evidence of these biases in their products.
I asked him to join me in a simple experiment. We used their company’s own AI assistant to search for information about “successful entrepreneurs” and then for “successful Black entrepreneurs.” The first search returned dozens of results with no qualifiers. The second search returned significantly fewer results, all explicitly labeled as “Black entrepreneurs” rather than just “entrepreneurs.”
The room fell silent as everyone recognized what had happened — success was being coded as white by default in their system. What made this moment powerful wasn’t just identifying the bias, but watching the executive’s reaction evolve from denial to recognition to commitment. By the end of the session, he had pulled out his phone to text his development team about implementing new testing protocols.
This experience reinforced for me that sometimes the most powerful way to create change isn’t through reports or statistics, but through simple demonstrations that make invisible biases visible. It also showed how quickly people can shift from resistance to advocacy when they witness the impact of these issues.
You are a successful leader in the AI space. Which three character traits do you think were most instrumental to your success? Can you please share a story or example for each?
Curiosity has been central to my journey in AI. When I first read McKinsey’s report showing how generative AI could widen the racial wealth gap by $43 billion annually if left unchecked, I didn’t simply accept this as fact. I wanted to understand why and how this happens. This curiosity led us to conduct our nationwide “Navigating Biases in Generative AI” survey, which revealed public concerns about racism, sexism, and classism in AI. By asking questions others weren’t asking, we uncovered insights that now guide our work with clients.
Adaptability has allowed me to pivot as technology evolves. When we noticed how many organizations were adopting AI without considering its impacts, we transformed Better Together Agency into an AI-forward communications agency. This required learning new skills, building new frameworks, and sometimes admitting what we didn’t know. For example, when a client asked us to help them communicate about their AI tool that was producing biased results, we had to quickly adapt our approach to address the communications challenge and help them understand the technical aspects of bias mitigation.
Persistence has been crucial when confronting systemic issues in technology. As a Black woman in communications, I’ve encountered resistance when highlighting bias in AI systems. When we published our findings on AI bias, some technology companies dismissed our concerns. Rather than backing down, we continued gathering data, building case studies, and demonstrating the business value of addressing these issues. Eventually, those same companies came to us for guidance on creating more inclusive AI strategies.
Let’s jump to the primary focus of our interview. Can you share a specific example of how you or your organization used AI to solve a major business challenge? What was the problem, and how did AI help address it?
Better Together Agency faced a challenge common to many communications agencies: how to provide clients with data-backed strategies while maintaining a human-centered approach. The problem was twofold: We needed to analyze vast amounts of information about public perception of AI technologies, but we also needed to identify patterns of bias that might not be obvious through traditional research methods.
We created a hybrid approach using AI tools to develop personas and analyze public sentiment across social media, articles, and forums about generative AI technologies. The AI helped us process thousands of conversations and identify key themes around bias concerns that would have taken months to analyze manually.
This approach was successful because we didn’t rely solely on the AI analysis. We combined the AI-generated insights with human expertise, conducting additional qualitative research with diverse focus groups to verify and contextualize what the AI had found.
The result was our “Navigating Biases in Generative AI” report, which provided clients with actionable insights about public concerns regarding AI bias. This approach solved our business challenge by allowing us to offer clients strategies based on comprehensive data while maintaining the human perspective essential to communications work.
One client, a technology company developing an AI-powered recruiting tool, used our insights to identify and address potential bias points in their algorithm before launch. This prevented a potential reputation crisis and improved their product, demonstrating how AI can solve problems combined with human oversight.
What are some of the common misconceptions you’ve encountered about using AI in business? How do you address those misconceptions?
One persistent misconception is that AI is too complex for non-technical teams to use or understand. Many business leaders believe they need data scientists or engineers on staff to benefit from AI. In reality, many AI tools today are designed with user-friendly interfaces that allow people with various backgrounds to leverage them. We address this by showing clients practical examples of how communications teams can use AI tools for content analysis, audience research, and campaign optimization without technical expertise.
Another misconception is that AI will produce perfect results without human input. Some clients come to us expecting AI to solve all their problems automatically. We clarify that AI is a tool that requires human guidance, judgment, and oversight. We demonstrate this by showing examples where AI outputs reflected biases in training data, emphasizing that human review is essential to catch these issues.
A third misconception is that AI is an all-or-nothing proposition — either you transform your entire business or don’t use it at all. We help clients understand that AI adoption can be incremental, starting with specific use cases that address clear business needs. For a nonprofit client concerned about resource constraints, we implemented a simple AI tool to analyze donor communications, which improved their fundraising without requiring a major technological overhaul.
By addressing these misconceptions with practical examples and clear explanations, we help organizations develop realistic expectations about what AI can do for their business and how to implement it responsibly.
In your opinion, what is the most significant way AI can make a positive impact on businesses today?
The most significant way AI can positively impact businesses today is by creating human-agent hybrid teams that increase productivity while allowing employees to focus on high-value work.
This transformation happens because AI provides “intelligence on tap” that works across organizations to handle routine tasks, analyze data, and generate insights quickly. When businesses integrate AI agents into their workflows, they create a new organizational model that remains human-led but operates with AI assistance.
As my agency works to become AI-Forward and incorporates these tools into our workflows, we’ve started seeing these results:
- Employees accomplish more work and tackle bigger challenges
- Teams find more satisfaction in their daily tasks
- Companies operate with greater agility
- Workers experience less burnout
- Organizations grow without adding as many new staff members
This approach changes how work happens. AI agents function as digital colleagues that expand what humans can do, allowing people to concentrate on creative, strategic, and interpersonal aspects of work.
As a small business owner, I know that other companies can now build successful businesses by using AI to handle market research and customer service. Large companies use AI to improve supply chains, increase profits, and manage core business functions with smaller teams.
Success comes from finding the right balance between human and AI capabilities. AI offers unlimited capacity, constant availability, and processes vast information, while humans provide judgment, creativity, and strategic thinking.
As technology continues to advance, successful organizations will view AI as a partner in creating value and helping people reach their potential.
Based on your experience and research, can you please share “5 Ways AI Can Solve Complex Business Problems”? These can be strategies, insights, or tools that companies can use to make the most of AI in addressing their challenges.
1. Rather than replacing humans, AI works best when paired with human creativity and judgment. These collaborative teams combine AI’s processing power with human empathy and strategic thinking. For a reproductive rights campaign, we developed a workflow where AI agents handled research, content drafting, and performance analytics, while our human team focused on storytelling, relationship building, and strategic direction. This human-agent collaboration allowed us to produce three times the content with the same team size, reaching more communities with personalized messaging. The AI handled data-heavy tasks while our team provided the emotional intelligence and cultural context essential for sensitive topics.
2. AI excels at analyzing massive datasets that would overwhelm human analysts, identifying patterns and trends that drive better decision-making. We used Notebook LM to process enormous datasets from academic journals for a reproductive rights client. Using the generative AI tool, we turned complex research into a 15-minute podcast to quickly learn everything needed to draft an op-ed. This allowed us to include compelling data points in the op-ed, making it more likely to receive media coverage. The AI-assisted research process reduced our preparation time from days to hours while ensuring we captured the most relevant information for our advocacy work.
3. AI helps us make expertise available across the agency, breaking down traditional departmental boundaries. Like what Supergood (an AI-native creative agency) has accomplished, we’ve created a platform that puts strategic communications research at every employee’s fingertips. We don’t need a strategist on every brief; everyone at Better Together Agency can access that expertise via our platform. This democratization of knowledge has allowed our teams to work more fluidly across disciplines. For a recent LGBTQIA+ rights campaign, team members from different backgrounds could access specialized knowledge through our AI platform, creating more comprehensive and effective messaging strategies.
4. AI helps us anticipate client needs and campaign outcomes, allowing for more proactive strategic planning. We’ve implemented AI-powered sentiment analysis tools to monitor real-time public response to our clients’ social campaigns. For a worker rights initiative, this technology allowed us to track how different messages resonated across various communities and quickly adjust our approach based on the data. The predictive capabilities helped us identify emerging narratives around labor issues before they gained mainstream traction, giving our client time to prepare thoughtful responses. This proactive approach strengthened the campaign’s effectiveness and demonstrated our commitment to data-driven advocacy.
5. AI tools help us produce higher-quality content faster, allowing our team to focus on strategy and client relationships. We’ve integrated Canva Magic Write and Jasper AI into our content creation process for social justice campaigns. For a climate action initiative, these tools helped us quickly generate multiple content variations tailored to different platforms and audiences. Our human team then refined the messaging to ensure it aligned with our client’s voice and values. This approach reduced content creation time by 40% while maintaining the authentic, purpose-driven tone that defines our work. The AI tools handle the first drafts, allowing our creative team to focus on adding the human touch that makes content truly resonate.
How can smaller businesses or startups, with limited budgets, begin to integrate AI into their operations effectively?
Small businesses can start their AI journey without big investments by focusing on specific areas that will bring quick wins. Begin with free or low-cost AI tools that address your most pressing needs. For example, customer service chatbots can handle routine questions 24/7, freeing up your team for complex issues.
Look for AI solutions with flexible pricing that let you start small and scale up as you see results. Many platforms offer tiered pricing or free versions with basic features. Cloud-based AI tools often require minimal setup and technical expertise, making them perfect for small teams.
Consider these practical steps:
- Identity one business process that’s repetitive or time-consuming
- Research AI tools specifically designed for that function
- Start with a small pilot project to test results
- Collect feedback and measure improvements
Remember that AI doesn’t have to replace your existing systems. Many tools integrate with popular business software you might already use. This approach lets you add AI capabilities gradually without disrupting your operations
What advice would you give to business leaders who are hesitant to adopt AI because of fear, misconceptions, or lack of understanding?
Start by separating facts from fiction about AI. Many leaders worry about complexity, cost, or job displacement, but the reality is that AI works best as a complement to human skills, not a replacement.
Begin with low-risk experiments. Try using AI as a thought partner to generate ideas or test different approaches. This hands-on experience will build familiarity and confidence without major commitments.
Education is crucial for overcoming resistance. I’ve seen companies successfully introduce AI by offering workshops that demonstrate practical applications and benefits. When people understand how AI can make their work more interesting by handling routine tasks, resistance often turns to enthusiasm.
Find a small project where AI can solve a real business problem, then document the results. Success stories from within your organization are powerful for building buy-in. One manufacturing client started with just one AI application for quality control, and the clear ROI quickly convinced skeptical executives to explore more uses.
Remember that AI adoption isn’t all-or-nothing. You can introduce it gradually, focusing on areas where it makes the most sense for your business. This measured approach helps manage change while still moving forward.
Finally, stay focused on business outcomes rather than technology for its own sake. The question isn’t “How can we use AI?” but “What business problems can AI help us solve?” This practical mindset keeps AI initiatives grounded in real value.
In your opinion, how will AI continue to shape the business world over the next 5–10 years? Are there any trends or emerging innovations you’re particularly excited about?
The next decade will see AI transform from a competitive advantage to a business necessity. We’re moving toward what Microsoft calls “Frontier Firms” — organizations built around on-demand intelligence and human-AI collaboration.
Three major shifts will define this transformation:
First, AI will break down traditional organizational silos. When expertise becomes available on demand through AI, companies can form dynamic teams around specific goals rather than rigid departments. This mirrors the movie production model, where specialized teams come together for projects and then reconfigure as needed.
Second, we’ll see the rise of “human-agent teams” where AI handles routine tasks while humans focus on judgment, creativity, and complex decision-making. According to Microsoft’s 2025 Work Trend Index, 46% of organizations already use AI to fully automate certain workflows.
Third, AI will democratize access to capabilities that were once available only to large corporations. Small companies will compete more effectively when they can access sophisticated analytics, automation, and insights without massive investments.
I’m particularly excited about agentic AI systems that can work across multiple applications to complete complex workflows. These systems will transform enterprise applications like CRM and ERP by enabling real-time, data-driven decision-making at scale.
Another promising area is AI’s potential to accelerate innovation cycles. By automating parts of the R&D process and generating novel solutions, AI will help companies bring new products to market faster than ever before.
How do you think the use of AI to solve business problems influences relationships with customers, employees, and the broader community?
AI is reshaping relationships across all stakeholders in ways that can be transformative when implemented thoughtfully.
For customers, AI enables personalization at scale. Companies can now provide tailored experiences that were previously impossible with human resources alone. Research shows 64% of business owners believe AI will improve customer relationships. The key is using AI to augment human service rather than replace it completely. Customers appreciate quick, accurate responses from AI for routine matters, but still want human connection for complex or emotional issues.
For employees, AI is changing the nature of work itself. When AI handles repetitive tasks, employees can focus on more creative, strategic work. Microsoft’s research found that workers at AI-forward companies report more opportunities for meaningful work (90% compared to 73% globally) and greater optimism about future opportunities (93% versus 77%).
The broader community benefits when AI addresses societal challenges. For example, AI can improve access to services in underserved areas, reduce environmental impact through optimization, and create new economic opportunities. Mastercard exemplifies this approach by running AI projects targeting community development and building data science talent in underserved areas.
The most successful organizations view AI as a tool for human empowerment rather than replacement. When implemented with this mindset, AI can strengthen relationships by creating more value, solving problems more effectively, and allowing for more meaningful human interactions.
You are a person of great influence. If you could start a movement that would bring the most amount of good to the most amount of people through AI, what would that be? You never know what your idea can trigger. 🙂
I would start a movement focused on “Inclusive AI” — making artificial intelligence accessible, beneficial, and representative for all communities, especially those historically left behind by technological advances.
This movement would have three core pillars:
First, education and access. We would create free, accessible learning programs to help people from all backgrounds understand and use AI effectively. These would range from basic literacy for everyday users to advanced training for those interested in AI careers. By removing barriers to entry, we could ensure that the benefits of AI aren’t limited to those who already have advantages.
Second, diverse development. We would push for AI systems to be built by diverse teams and trained on inclusive data. This would help prevent the biases we’ve already seen emerge in AI systems. When AI is developed by people with varied perspectives and experiences, it better serves the needs of all communities.
Third, community-focused applications. We would prioritize AI projects that address pressing social needs — from improving healthcare access in rural areas to creating economic opportunities in underserved communities. By focusing AI development on solving real problems that affect millions of people, we could demonstrate technology’s potential for positive impact.
The ultimate goal would be to transform AI from something that many people fear will widen existing divides into a force that actually helps create a more equitable society. By bringing together technologists, community leaders, educators, and policymakers, we could ensure that AI’s benefits are widely shared.
How can our readers further follow you online?
Readers can connect with me on LinkedIn at https://www.linkedin.com/in/cnmontgomery. For more about our work at Better Together, visit our website at thebettertogetheragency.com or follow our company LinkedIn page at https://www.linkedin.com/company/thebettertogetheragency.
I’m always open to conversations about how organizations can use AI ethically and effectively, so feel free to reach out directly at catharine@thebettertogetheragency.com.
This was great. Thank you so much for the time you spent sharing with us.
About the Interviewer: Chad Silverstein is a seasoned entrepreneur with 25+ years of experience as a Founder and CEO. While attending Ohio State University, he launched his first company, Choice Recovery, Inc., a nationally recognized healthcare collection agency — twice ranked the #1 workplace in Ohio. In 2013, he founded [re]start, helping thousands of people find meaningful career opportunities. After selling both companies, Chad shifted his focus to his true passion — leadership. Today, he coaches founders and CEOs at Built to Lead, advises Authority Magazine’s Thought Leader Incubator.
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