AI Meets Reality

Guest LinkedIn: J-Ann Tio Toles | LinkedIn

Podcast Key Takeaways:

AI Adoption Starts with Business Needs

J-Ann Tio Toles emphasizes that successful AI initiatives begin with understanding real business workflows and challenges, not simply deploying technology for technology’s sake. The most impactful solutions are grounded in operational realities and measurable outcomes.

Empowering Employees Drives Adoption

Arrive Logistics has invested in building AI literacy across the organization by supporting both AI-curious employees and AI enthusiasts. Through internal workshops, committees, and role-specific tools, employees are encouraged to explore practical ways AI can enhance their day-to-day work.

Embedding Technologists Accelerates Innovation

By placing engineers directly alongside business teams, Arrive has created faster feedback loops and stronger collaboration between users and developers. This approach enables rapid prototyping, quicker problem-solving, and solutions that are closely aligned with business needs.

Governance and Prioritization Are Essential

While AI can solve many problems, not every use case is worth pursuing. The discussion highlights the importance of disciplined prioritization, governance, and ROI-focused decision-making to ensure AI investments deliver meaningful value.

Build vs. Buy Requires Strategic Balance

Organizations must carefully evaluate where to invest internal resources and where to leverage best-in-class vendors. Arrive’s approach focuses on building capabilities tied to core business differentiators while partnering externally for specialized technologies.

Rapid Experimentation Creates Competitive Advantage

The conversation explores how AI is enabling teams to build, test, and refine solutions faster than ever before. By embracing a “move quickly, fail fast” mindset, organizations can accelerate innovation while continuously improving their AI-driven solutions.

Guest LinkedIn: Jenn Hartfield | LinkedIn

Podcast Key Takeaways:

Responsible AI Starts with Culture:

Jenn Hartfield emphasizes that successful AI governance is about more than policies and controls. Organizations that scale AI effectively create a culture of responsible AI through education, collaboration, and shared accountability across teams.

Governance Should Enable Innovation

Rather than acting as a barrier, governance can provide the guardrails that allow teams to innovate confidently. By defining clear risk thresholds and expectations, organizations can support experimentation while managing compliance and operational risks.

AI Literacy Is Critical for Adoption

Building AI literacy across the organization helps employees understand both the opportunities and risks associated with AI. Meeting people where they are and creating opportunities for continuous learning can drive responsible adoption at scale.

Community and Collaboration Drive Better Outcomes

The conversation highlights the value of cross-functional collaboration and knowledge sharing. Creating communities where employees exchange ideas, insights, and lessons learned helps organizations stay informed and adapt to a rapidly changing AI landscape.

Organizations Must Plan for the Economics of AI

As AI adoption grows, leaders must consider the full cost of implementation, including model consumption, infrastructure, guardrails, and monitoring. Strategic planning and prioritization are essential to ensure AI investments deliver meaningful business value.

What Happens When AI Moves Into the Physical World?

Jenn shares her perspective on the future of physical AI and the new questions it could create around safety, accountability, and human interaction. The conversation ventures beyond today's governance challenges to explore how organizations may need to prepare for a future where intelligent systems operate not just on screens, but alongside people in the real world.

Guest LinkedIn: J-Ann Tio Toles

Podcast Key Takeaways:

AI Adoption Starts with Business Needs

J-Ann Tio Toles emphasizes that successful AI initiatives begin with understanding real business workflows and challenges, not simply deploying technology for technology’s sake. The most impactful solutions are grounded in operational realities and measurable outcomes.

Empowering Employees Drives Adoption

Arrive Logistics has invested in building AI literacy across the organization by supporting both AI-curious employees and AI enthusiasts. Through internal workshops, committees, and role-specific tools, employees are encouraged to explore practical ways AI can enhance their day-to-day work.

Embedding Technologists Accelerates Innovation

By placing engineers directly alongside business teams, Arrive has created faster feedback loops and stronger collaboration between users and developers. This approach enables rapid prototyping, quicker problem-solving, and solutions that are closely aligned with business needs.

Governance and Prioritization Are Essential

While AI can solve many problems, not every use case is worth pursuing. The discussion highlights the importance of disciplined prioritization, governance, and ROI-focused decision-making to ensure AI investments deliver meaningful value.

Build vs. Buy Requires Strategic Balance

Organizations must carefully evaluate where to invest internal resources and where to leverage best-in-class vendors. Arrive’s approach focuses on building capabilities tied to core business differentiators while partnering externally for specialized technologies.

Rapid Experimentation Creates Competitive Advantage

The conversation explores how AI is enabling teams to build, test, and refine solutions faster than ever before. By embracing a “move quickly, fail fast” mindset, organizations can accelerate innovation while continuously improving their AI-driven solutions.

Guest LinkedIn: Jolanta Pomiotlo | LinkedIn

Podcast Key Takeaways:

Start with the Business Problem

Jolanta Pomiotlo emphasizes that organizations should not pursue AI for its own sake; the best results come from identifying a real business problem first and then applying the right technology to solve it.

Strong Data Foundations Enable AI Success

The conversation highlights that data quality, context, and governance are essential to moving AI initiatives beyond pilot mode and into production, since poor or fragmented data leads to poor outcomes.

Start Small to Build Momentum

Rather than beginning with large, complex AI initiatives, the episode stresses the value of starting with smaller, more manageable use cases where data is stronger and value can be demonstrated quickly.

Change Enablement Drives Adoption

Successful AI rollout depends on tailored training, change champions, and helping employees rethink how they approach their work, while addressing resistance and building confidence in the tools.

Governance and Security Must Come First

As AI tools become embedded in daily workflows, organizations need clear guardrails around permissions, sensitive data, and platform governance to ensure secure and responsible use.

AI Accelerates Productivity, Not Just Technology

The episode explores how AI can help teams prototype faster, reduce manual effort, and work through larger backlogs, ultimately enabling organizations to deliver value more quickly.

Guest LinkedIn: Fiona Towner | LinkedIn

Podcast Key Takeaways:

Practical AI Adoption Matters

Fiona Towner emphasizes that successful AI adoption starts with practical use cases, helping employees understand how the technology can support day-to-day work and deliver measurable value.

Peer Learning Accelerates Change

Organic, peer-to-peer knowledge sharing can be more effective than top-down training, building curiosity, confidence, and stronger adoption across the organization.

Agentic AI Is Reshaping Analytics

The conversation explores how AI agents are beginning to move users beyond static dashboards by enabling more dynamic analysis, recommendations, and action-oriented insights.

Trust and Governance Remain Critical

As AI becomes more embedded in workflows, organizations must balance speed and efficiency with validation, governance, and responsible use of data.

Strategy and Budget Must Align

Scaling AI requires leadership support, thoughtful investment, and a clear focus on where automation, copilots, or agents can create the greatest business impact.

Guest Notes

Erika Albert is the program strategist for major and principal gifts at ALSAC, the fundraising and awareness organization for St. Jude Children’s Research Hospital. In her role, she builds relationships with donors, develops fundraising strategies, and helps secure critical support to advance St. Jude’s mission of providing free care and advancing pediatric research.

Guest LinkedIn: Erika Albert

Podcast Key Takeaways

Personal Connection Drives Mission

Erika Albert’s experience as a childhood cancer survivor deeply informs her passion and commitment to fundraising for St. Jude Children’s Research Hospital.

AI Enhances Fundraising

The use of AI tools, such as Copilot and ChatGPT, helps Erica and her team streamline donor research, personalize outreach, and summarize complex medical information, slowing them to focus on building authentic relationships.

Balancing Technology and Humanity

While AI offers efficiency, maintain genuine human connection with donors remain essential, especially in the era of increasing autonomation and skepticism about authenticity.

Ethical and Data Challenges

The team faces ongoing challenges around data privacy, model accuracy, and ethical use of donor information, highlighting the importance of responsible technology adoption in philanthropy

St. Jude’s Global Impact

St. Jude’s work extends beyond patient care, with innovative genomics research and international collaboration accelerating program progress in pediatric cancer treatment and benefiting children worldwide.

Guest LinkedIn

Carlin Power, MBA | LinkedIn

Key Takeaways:

Educate: Spark Curiosity and Confidence

JLL began its AI journey by inspiring experimentation and providing practical training, making AI approachable and relevant for every employee.

Define Strategy: Connect Vision to Impact

A clear, company-wide AI strategy - centered on measurable goals and consistent messaging - ensured that every initiative aligned with business outcomes.

Lay the Foundation: Build Security and Trust

JLL prioritized data security, privacy, and governance from day one, creating a trusted environment for safe and scalable AI adoption.

Prepare Your People: Empower and Engage

Continuous feedback, tailored training, and user-centric design enabled employees to confidently adopt, use, and shape AI tools in their daily work.

Go & Grow: Sustain Momentum and Scale Innovation

JLL is investing in agentic AI and citizen development, scaling expertise and empowering teams to create future-ready solutions that drive ongoing impact.