Blueprint for Reimagining Workflows & Building AI-Native Ecosystems
Speakers
I'm a seasoned executive with 30+ years of experience in driving data innovation and solution-based sales strategies. I am currently the Senior Vice President of Global Sales and Data Solutions at Straive, recognized as a leading voice for Women in Data and AI.
Known for my leadership in both established and emerging markets, I have built a reputation for crafting value-driven, cost-effective solutions that empower clients across industries, including BFS (Portfolio and Asset Management), Pharma & Lifesciences, Manufacturing & Logistics, Media and Entertainment
With a consultative approach and a passion for innovation, I help enterprises accelerate their data and AI journeys, driving both ROI and exceptional customer experiences. Leading a global team with a highly localized focus, I help Straive deliver impactful solutions across North America, Europe, and Asia.
Rick Fordyce is Chief Data Officer at MediaRadar, leading enterprise data strategy, governance, and AI-driven innovation. He specializes in transforming data operations into scalable, high-quality, revenue-impacting platforms. With a track record of driving large-scale organizational change and operational efficiency, Rick aligns people, process, and technology to unlock measurable business value. He is passionate about building data cultures that are powered by AI, perfected by people, and proven in quality.
SUMMARY
This session presents a real-world case study of how a data-driven media company transformed its operations using AI to unlock scale, efficiency, and new revenue opportunities. Facing legacy workflows, fragmented data, and heavy reliance on manual processes, the organization shifted from a labor-intensive model to an AI-enabled system with humans in the loop. By focusing on a clear entry point, building strong data governance, and prioritizing quality alongside scale, the team was able to dramatically increase coverage, accelerate time to market, and win new business. The key takeaway is that successful AI adoption is not just about automation. It is about redesigning workflows, empowering people, and turning data into actionable insights that drive growth.
TRANSCRIPT
[00:00 – 00:01:30] Introduction & Context The session introduces an AI and data services company working with a media client undergoing transformation under new leadership and private equity ownership.
[00:01:30 – 00:02:30] The Initial Challenge: Legacy & Fragmentation The organization faced common issues including inconsistent data, siloed processes, heavy reliance on institutional knowledge, and limited scalability.
[00:02:30 – 00:03:30] The Breaking Point: Human-Dependent Scaling Expanding coverage required massive manual effort, with estimates of hundreds of people and significant cost just to process historical data.
[00:03:30 – 00:04:30] Starting Small: Finding the First Use Case Rather than attempting a full transformation, the team focused on a specific, high-value entry point where data directly impacted customers.
[00:04:30 – 00:05:30] Building the Classification Engine AI was introduced to classify and extract key information from ads, enabling faster and more scalable data processing.
[00:05:30 – 00:06:30] The Importance of Data Governance Early results showed that AI performance depended heavily on clean, well-structured data. Governance and data strategy became critical foundations.
[00:06:30 – 00:07:30] Human-in-the-Loop Model Employees transitioned from manual data entry to validating AI outputs, ensuring quality while increasing efficiency.
[00:07:30 – 00:08:30] Unlocking New Insights from Data AI enabled deeper analysis beyond basic classification, surfacing trends and insights that were previously inaccessible.
[00:08:30 – 00:09:30] Measuring Success: Beyond Cost Savings The initiative drove faster onboarding, expanded data coverage, and contributed to winning major new customer deals.
[00:09:30 – 00:10:30] Change Management & Culture Shift Adoption required addressing employee concerns, retraining teams, and positioning AI as an augmentation tool rather than a replacement.
[00:10:30 – 00:11:30] A New Operating Model The organization reframed itself as a data company powered by AI but perfected by people, combining automation with human expertise.
[00:11:30 – 00:12:30] Scaling Forward: What’s Next The focus shifts to expanding into new datasets and markets, leveraging AI to handle increasing data volume and complexity.
[00:12:30 – 00:13:30] Key Takeaway: Speed and Adaptability AI enables faster delivery and iteration, allowing organizations to keep pace with rapidly evolving data environments.
