InnoTech 2025 Conference Recap
The 2025 InnoTech Conference brought together technology professionals, industry leaders, and innovators to examine how artificial intelligence (AI), cloud strategy, and digital transformation are reshaping enterprise IT. Across the six sessions I attended, presenters offered deep insights into the evolving balance between innovation, governance, and value creation. As a project manager working in IT, I attended each discussion to better understand the emerging challenges and opportunities in cloud adoption, AI-driven program management, and workforce evolution. The conference emphasized the importance of strategic decision-making, adaptability, and leadership as organizations modernize systems and redefine digital operations.
Session: InnoTech Morning Keynote – Unleashing AI: Why Enterprises Are Breaking Free from the Cloud Oligopoly
Session: Protecting Your Trade Secrets in an Era of AI
Session: Managing & Modernizing Legacy Systems While Innovating
Session: How IT Leaders Can Build Real Value with AI and Program Management
Session: IT Leadership in an Age of Emerging Technologies and AI
Session: How Organizations Are Transitioning, Upskilling, and Evolving in the AI Workforce for 2026
Personal Reflections on Leadership and Project Management
Personal Application to Career Development
Session Recaps
InnoTech Morning Keynote – Unleashing AI: Why Enterprises Are Breaking Free from the Cloud Oligopoly
Speaker: David Linthicum
David Linthicum explored how enterprises are rethinking their dependency on major hyperscalers such as AWS, Microsoft, and Google. He argued that vendor lock-in, rising costs, and compliance risks are pushing companies toward “neo-clouds,” sovereign clouds, and private colocation models that offer greater flexibility and control. Linthicum noted that many enterprises mistakenly assume cloud providers handle all compliance responsibilities. He cited HIPAA fines and data residency violations as proof that organizations must retain accountability over their infrastructure.
His discussion on “cloud repatriation” resonated with me as a project manager balancing cost efficiency with innovation. Linthicum’s message - that hybrid and multi-cloud architectures will dominate the next phase of AI adoption - illustrated the growing importance of flexibility in enterprise architecture. He urged leaders to challenge the status quo, renegotiate egress fees, and pursue heterogeneous architectures tailored to each workload’s value to the business.
Protecting Your Trade Secrets in an Era of AI
Speakers: Greg Starling, Blake Dailey, Blake Holman, Carl Sinclair
This panel examined how rapid AI adoption affects data privacy and intellectual property. The speakers agreed that organizational readiness and data governance are the first lines of defense. Starling described “shadow AI” risks where employees use public tools such as ChatGPT or Gemini without safeguards, potentially exposing proprietary code or client data.
The discussion highlighted the need for structured AI policies, employee education, and secure enterprise implementations like ChatGPT Enterprise or Microsoft Copilot. Holman emphasized balancing preventive and detective controls, comparing it to the evolution of security from network firewalls to modern data classification. As a project manager, I saw parallels between governance in security and process control in project execution - both require continuous monitoring and accountability, not just policy creation.
Managing & Modernizing Legacy Systems While Innovating
Speakers: Alan White, Brad Smith, Victor Carneiro, Daniel Yunker
This session focused on the tension between modernization and maintaining operational stability. Brad Smith from Paycom stressed that innovation should not compromise uptime or reliability. Carneiro of HealthChoice Oklahoma described legacy modernization as a “change management problem disguised as technology,” reminding leaders that modernization projects fail more often due to poor communication than bad code.
Panelists discussed modular modernization - replacing systems incrementally through APIs and containerization instead of full rebuilds. Yunker’s experience at Kimray illustrated how innovation can succeed within legacy environments through careful project phasing and cross-department collaboration. The insights reinforced the project management principle of balancing scope, cost, and time while maintaining business continuity.
How IT Leaders Can Build Real Value with AI and Program Management
Speaker: Nayeem Ahmed
Nayeem Ahmed from InterWorks argued that AI should enhance - not replace - program management discipline. He presented a framework where AI augments reporting, forecasting, and risk identification through pattern recognition and automation. Ahmed emphasized measurable value creation, advocating for pilot projects with clear KPIs before scaling AI initiatives.
This aligned directly with my own approach to managing IT transformation projects. Ahmed’s focus on integrating AI analytics into program governance mirrors my current push to use data visualization tools to track risk exposure and resource utilization. The takeaway: AI is a multiplier of good management but cannot fix poor leadership or process immaturity.
IT Leadership in an Age of Emerging Technologies and AI
Speakers: Chris Scully, Kevin Chambers, Joe Bowersox, Mike Wood, Dan Murray
This leadership panel discussed how digital transformation is reshaping the CIO’s role. Scully opened by describing leadership as “strategic adaptability,” noting that technology leaders must manage uncertainty while maintaining trust across their teams. Chambers from Bethany Children’s Health Center discussed balancing innovation with compassion in healthcare IT, where technology directly affects patient outcomes.
Mike Wood and Joe Bowersox emphasized the cultural side of leadership - building teams that embrace experimentation but respect governance. The panel’s recurring theme was ethical responsibility: the obligation to deploy emerging technologies thoughtfully. For me, this underscored how modern project management extends beyond delivery schedules to include ethical and organizational implications of technology adoption.
How Organizations Are Transitioning, Upskilling, and Evolving in the AI Workforce for 2026
Speakers: Jalen Byford, Hursh Juneja, John Marcellus
The final session addressed workforce transformation as AI changes job roles and expectations. Byford emphasized the importance of reskilling rather than replacement, noting that successful organizations invest in AI literacy across all departments. Juneja described Chickasaw Nation’s structured training programs for IT employees, built around internal mentorship and cross-functional learning.
John Marcellus added that technical expertise alone is insufficient; soft skills such as critical thinking, adaptability, and communication are now essential complements to automation. As someone managing diverse technical teams, this message reinforced the need to guide - not just assign - team members through change.
Personal Reflections
Reflections on Leadership and Project Management
Throughout the conference, I reflected on how each session connected to my work as an IT project manager. Linthicum’s keynote challenged my assumptions about “defaulting” to cloud vendors, pushing me to think critically about cost efficiency and long-term sustainability. The security panel reinforced the necessity of governance frameworks that protect sensitive data, much like risk registers safeguard project outcomes.
The modernization and AI value sessions both emphasized incremental, data-driven approaches - principles that parallel agile methodologies. I recognized that my success as a project manager depends on fostering a culture of accountability and continuous improvement rather than reacting to trends. The leadership and workforce sessions reminded me that technology adoption is ultimately a human challenge: leading with empathy, transparency, and trust creates alignment between innovation and execution.
Application to Career Development
The InnoTech Conference directly influenced my professional development goals. As I pursue advanced certifications in project management and AI, I plan to apply the following lessons:
Architectural Awareness – Evaluate multi-cloud and sovereign cloud options to reduce vendor dependency and optimize project budgets.
Data Governance Leadership – Implement clear policies for AI usage across teams, focusing on training and documentation.
Incremental Modernization – Lead modernization projects with phased implementation plans tied to measurable outcomes.
Ethical AI Deployment – Advocate for transparency in AI-driven decisions affecting clients and internal teams.
Upskilling Strategy – Mentor staff through AI adoption by combining technical learning with communication and critical thinking development.
These actions align with my broader goal of becoming a more strategic project leader - one who not only manages tasks but also shapes organizational capability for long-term digital transformation.
References:
Ahmed, N. (2025, April). How IT leaders can build real value with AI and program management. InnoTech Conference, Oklahoma City.
Byford, J., Juneja, H., & Marcellus, J. (2025, April). How organizations are transitioning, upskilling, and evolving in the AI workforce for 2026. InnoTech Conference, Oklahoma City.
Linthicum, D. (2025, April). Unleashing AI: Why enterprises are breaking free from the cloud oligopoly. InnoTech Conference, Oklahoma City.
Scully, C., Chambers, K., Bowersox, J., Wood, M., & Murray, D. (2025, April). IT leadership in an age of emerging technologies and AI. InnoTech Conference, Oklahoma City.
Smith, B., White, A., Carneiro, V., & Yunker, D. (2025, April). Managing and modernizing legacy systems while innovating. InnoTech Conference, Oklahoma City.
Starling, G., Dailey, B., Holman, B., & Sinclair, C. (2025, April). Protecting your trade secrets in an era of AI. InnoTech Conference, Oklahoma City.