August 2026: TechTalk Newsletter
August 2026: TechTalk Newsletter
In this issue, we explore what it takes to turn AI ambition into business value, from cloud and data readiness to cost visibility, governance, and smarter technology decisions. Explore this month's insights and see how these priorities support scalable AI success.
Are Your AI Investments Delivering Business Value?
Everyone is talking about AI. Fewer are talking about what happens when usage scales.
From token consumption and model costs to governance and accountability, AI introduces a new layer of financial complexity that many organizations aren't prepared for. As copilots, intelligent agents, and generative AI tools become part of everyday business operations, leaders need greater visibility into how AI investments are being consumed and whether they're delivering measurable value. FinOps for AI is helping organizations bring financial accountability to AI initiatives while maintaining the flexibility needed to innovate.
Much like cloud spending reshaped IT financial management, AI is creating a new category of consumption-based investment that requires ongoing oversight and optimization. Organizations that establish the right governance frameworks early can better manage costs, align AI initiatives with business objectives, and confidently scale adoption across the enterprise. The goal isn't to limit innovation. It's to ensure every AI investment supports a meaningful business outcome.
The challenge is that AI success isn't measured by adoption alone. Organizations need to understand which use cases are delivering results, where spending is increasing, and how to maintain governance as usage expands across teams. Many are discovering that traditional budgeting and cost management practices weren't designed for AI's rapidly changing consumption patterns. Gaining visibility into these trends can help leaders make more confident investment decisions, strengthen accountability, and create a clearer roadmap for scaling AI across the business.
The Cloud Decisions That Shape AI Outcomes
Understanding the cost of AI is important. Understanding whether your environment is prepared to support AI at scale may be even more important.
Many organizations are focused on deploying AI solutions as quickly as possible, but long-term success is often determined by decisions made well before the first AI workload goes into production. Cloud architecture, data accessibility, governance, and scalability all play a critical role in determining how effectively AI can be adopted across the business. The challenge isn't getting started with AI. It's building an environment that can support what's next.
Cloud modernization initiatives are creating an opportunity to rethink the foundations that will power future innovation. Decisions around Azure infrastructure, data strategy, and governance don't just influence today's workloads. They can impact how quickly teams can operationalize AI, scale new use cases, and respond to evolving business demands in the years ahead. Organizations that approach cloud transformation with AI in mind position themselves to move faster, adapt more easily, and create a stronger foundation for future growth.
Discover the cloud and infrastructure decisions that can either accelerate AI adoption or create barriers that are far more expensive to address later.
The Next Challenge: Governing AI Costs, Risk, and Complexity at Scale
Once organizations establish visibility into AI investments and build the infrastructure needed to support them, attention naturally shifts to a new challenge: maintaining control as adoption grows.
As AI capabilities spread across departments, the technology ecosystem supporting them becomes increasingly complex. Cloud resources, software licensing, data access, governance requirements, and security considerations all contribute to the total cost of delivering AI at scale. Without the right controls in place, organizations can find themselves managing overlapping investments, underutilized resources, and governance gaps that become more difficult to address over time.
That's why ITAM and FinOps are becoming increasingly connected within AI strategies. Together, they help organizations understand what technologies are being used, how they're being consumed, and where costs may be outpacing value. More importantly, they provide the visibility needed to make smarter decisions about future investments while reducing waste and mitigating risk.
The most successful organizations won't be those that simply deploy the most AI. They'll be the ones that create a sustainable framework for governing, optimizing, and scaling it. Learn how ITAM and FinOps can help turn AI growth into long-term business value.
Upcoming Events
Meet the Expert
Erik Moll, Lead Consultant – AI Productivity & Copilot Adoption
Erik Moll helps organizations turn the promise of AI into practical, measurable improvements in how people work. His focus is organizational AI: empowering individuals to use Microsoft 365 Copilot, work with specialized agents, and create their own declarative agents and skills. His consulting approach combines strategy with hands-on learning so clients can move from curiosity to confidence and from experimentation to sustainable adoption.
What is one piece of advice you would give businesses looking to improve their IT infrastructure, costs, or procurement strategy?
Do not start with the technology. Start with the business problem you are trying to solve.
The strongest technology investments are tied to clear outcomes and real user needs. That makes it easier to prioritize spending, drive adoption, manage change, and demonstrate value.
What is a common challenge you see clients facing, and how do you help solve it?
One of the biggest challenges I see is organizations asking, “How do we move beyond the AI hype and create real business value?” Employees may be eager to use AI but unsure where to start, while leaders want measurable outcomes and a clear return on investment.
I help bridge that gap by identifying high-impact use cases, building practical adoption plans, and equipping employees with the confidence and skills they need. One way I do this is through the 2.5-hour Copilot Inspiration Prompting Sessions I developed for new users, users of free Copilot experiences, and advanced licensed users.
Every session is tailored to the client, contains no slides, and centers on real business scenarios. Participants learn by doing and move from “I know what Copilot is” to “I know how I can use it tomorrow.”
What is the most rewarding part of your job?
The most rewarding part of my job is seeing the moment when someone realizes what is possible.
Whether it is a leader discovering a faster way to make decisions or an employee finding a way to save hours of repetitive work, I love helping people build confidence with AI and unlock better ways of working.
What's Top of Mind?
The Rise of Organizational AI
Much of the AI conversation focuses on developers building sophisticated agents and automations. An equally important shift is the emergence of organizational AI, where individuals are empowered to shape their own AI-enabled ways of working.
Through Microsoft 365 Copilot, employees can use first-party Copilot experiences, work with Microsoft-built agents such as Researcher and Analyst, and create their own declarative agents and skills. This gives employees new ways to research, analyze, create, and solve problems in the flow of work.
Operational AI remains critical. IT teams and developers will continue to build enterprise-grade declarative and agentic solutions that connect systems and automate complex processes. The organizations that lead will invest in both: operational AI to transform business processes and organizational AI to transform how people work.
My personal focus is enabling organizational AI. When employees receive practical, role-relevant experiences and permission to experiment responsibly, they stop seeing AI as a distant technology initiative and begin using it as a daily capability. That is where lasting adoption starts.
Schedule a 1:1 session with Erik