AWS re:Invent 2025: Agentic AI on the Rise

Introduction

In December 2025, AWS re:Invent took place in Las Vegas, Nevada. Key themes included the impact of Agentic AI, the benefits of AWS’s secure cloud and extensive toolkit, ongoing infrastructure innovations, and the growing role of developers in AI-driven solutions. AWS is shifting its strategic focus toward the promise of Agentic AI, AI systems capable of planning, executing, coordinating, and operating across the enterprise with minimal human instruction. Organizations are beginning to see meaningful ROI as these systems take on complex, goal-driven tasks while operating safely within defined guardrails.

In this Q&A, Liberty Advisor Group’s CTO, Scott Albrecht, shares where he sees Agentic AI delivering the greatest value and what enterprises must do to build true AI readiness.

While Agentic AI offers transformative potential, Scott emphasizes that its success depends on having the right infrastructure, clean data, and governance to keep systems aligned and prevent unintended outcomes.

2026 marks a shift toward Agentic AI, systems that operate more like teammates than tools.

What is the future of AI? 

The last three years have shown a clear evolution in how AI is understood and applied. In 2024, generative AI surfaced as the breakthrough technology with the promise of solving real business problems. By 2025, however, its limitations became clearer. GenAI was powerful but fundamentally static and sequential, great at producing content, not great at driving sustained business outcomes or operating as part of real workflows.

2026 marks a shift toward Agentic AI, systems that operate more like teammates than tools. These agents can take action, make decisions, and execute tasks autonomously, which is where organizations are finally seeing meaningful ROI. At the same time, we need to remain measured. Increased autonomy introduces the risk of unpredictable behavior, hallucinations, and operational noise if guardrails and governance aren’t in place.

A major theme this year was that the future of AI isn’t just more intelligence, it’s more reliable autonomy. But it’s also important to acknowledge that the agentic landscape is still young and evolving at a pace we haven’t seen in decades.

Recent studies show many organizations are changing their AI tooling quarterly as capabilities shift, new entrants appear, and some vendor promises fail to materialize in real-world settings. This volatility isn’t a sign of stagnation, it reflects a rapidly maturing space where flexibility is essential. Organizations that stay adaptable, evaluate continuously, and invest in architectures built to absorb change will be the ones who benefit most.

Ultimately, the future of AI lies in building trustworthy, resilient digital co-workers that integrate into systems, follow rules, and deliver measurable value, even as the ecosystem around them continues to evolve quickly.

Learn more about Liberty Advisor Group’s AI offerings.

What is the promise of Agentic AI?

Agentic AI represents a major shift from traditional programming to goal-driven, autonomous problem-solving. Instead of mapping out every scenario, you provide a goal, and the system determines how best to accomplish it. It does this through planning, tool use, memory, context awareness, and self-evaluation.

The real promise is in its ability to behave like a teammate. It doesn’t just execute commands, it evaluates options, runs scenarios, explains its choices, and provides recommendations for human oversight.

This makes it especially impactful in areas like supply chain, financial forecasting, inventory optimization, and customer operations, where conditions change constantly and decisions require ongoing context.

Another emerging advantage is scalability. Once an agent works for one use case, it can be cloned, adapted, and redeployed across additional workflows with far lower incremental cost than traditional automation. Combined with responsible guardrails, Agentic AI enables organizations to do more with less while keeping humans firmly in the decision loop.

What is the Power of Agentic AI 

The power of Agentic AI lies in its ability to move beyond rigid automation and take on dynamic, goal-oriented work. Unlike traditional RPA or workflow tools, which require exhaustive step-by-step definition, agents only need a goal. They autonomously plan, adjust, and execute tasks, and they can self-correct when conditions change.

This unlocks meaningful value:

• Operational efficiency: Agents handle the tedious calculations, reconciliations, and scenario-running that typically drain analyst capacity.
• Consistency and quality: Agents operate with precision, reducing human error and increasing repeatability.
• Faster decision cycles: Agents surface risks, opportunities, and options earlier, giving leaders more time to act.

With memory, contextual understanding, and self-evaluation, Agentic AI becomes a force multiplier for teams. Humans stay focused on judgment, exceptions, and strategy, while the agent does the operational heavy lifting.

What AI applications are noteworthy? 

We’re already seeing major AI applications reshape both business workflows and the creative landscape:

• Productivity & enterprise: Microsoft 365 Copilot, Salesforce Einstein GPT, SAP Joule, and Oracle NetSuite AI integrate intelligence directly into daily tasks and decision-making.
• AI cloud platforms: Salesforce AI Cloud and IBM Orchestrate enable cross-system orchestration and agentic workflows at scale.
• Creative systems: Adobe Firefly and Runway are redefining design, branding, and content creation.
• Conversational and reasoning models: ChatGPT, Anthropic Claude, and Google Assistant drive advanced reasoning and natural interaction.
• Developer tools: GitHub Copilot, AWS CodeWhisperer, and Kindo accelerate software engineering and reduce cycle time.

A key trend for 2026 is platform convergence. Instead of dozens of disconnected AI tools, organizations are shifting toward unified environments where orchestration, retrieval, governance, and observability work together. This reduces risk, simplifies compliance, and lowers total cost of ownership.

What is required to realize the benefits of AI?

To effectively leverage AI, organizations must build the right foundation:

1. Modern platforms: Legacy systems make AI integration difficult. Cloud ERPs like NetSuite, SAP S/4HANA, or QAD offer cleaner data structures and native AI features that accelerate adoption.
2. Clean, consistent data: AI depends on standardization. If terms like “inventory,” “location,” or “carry cost” aren’t defined and applied consistently, insight quality degrades quickly.
3. Governance & risk controls: As AI becomes more autonomous, organizations need clear policies for access, monitoring, traceability, and responsible use.
4. Operational readiness: Even with vendor-delivered AI, companies need internal expertise to integrate, secure, monitor, and iterate these systems.
5. Architectural flexibility: Because the agentic ecosystem is evolving so quickly, companies must design for change. Many organizations are already swapping out AI tools quarterly as capabilities advance or vendor expectations fall short. Vendor-neutral architectures, modular integrations, and strong governance ensure businesses can pivot quickly without disrupting operations or value creation.

Organizations with strong data foundations, flexible architectures, and thoughtful governance will be positioned to capture the full value of AI even as the market continues to shift.

What should companies be doing today to prepare for Agentic AI?

1. Identify operational areas where inefficiency, delay, or manual effort is creating measurable cost or risk. Agentic AI is most effective when tied to high-value, clearly defined pain points.
2. Modernize selectively, not all at once. You don’t need a full transformation to adopt AI. The systems closest to your target use cases should be cloud-ready, API-accessible, and capable of integrating with AI platforms.
3. Invest in data cleanup early. Standardized definitions, clean master data, and consistent process taxonomies significantly enhance AI accuracy and reduce implementation friction.
4. Build flexible, vendor-neutral architectures. Given the volatility in AI tooling, companies need integrations that can be swapped or extended with minimal disruption. Architectural rigidity will become a competitive disadvantage.
5. Establish governance and safety controls now. Define decision rights, auditing mechanisms, access policies, and boundaries for autonomous behavior. Autonomy must operate within rules, not outside them.
6. Upskill teams and build internal champions. The organizations realizing the greatest impact have analysts, operators, and architects who understand how to evaluate, test, and iterate with AI, even when the AI comes from a third-party vendor.
7. Pilot quickly, learn quickly. Short, targeted pilots reveal data issues, integration challenges, and operational opportunities faster than large-scale initiatives.

Companies that take these steps, grounded modernization, clean data, flexible architecture, strong governance, and rapid experimentation, will be prepared to capitalize on agentic systems as they continue to mature.

What is the ROI for AI

AI is already delivering significant returns across industries as companies move from experimentation to operational deployment:

• Sports: Thursday Night Football uses AI for real-time defense alerts, pocket health evaluation, and tactical analysis.
• Retail: AI-powered recommendation engines and chat experiences improve conversions and reduce service costs.
• Aerospace: Blue Origin uses agentic workflows for design, simulation, engineering assistance, and internal automation.
• E-commerce & logistics: Amazon uses AI for address prediction, specification-based development, automated testing, and robotics-enabled fulfillment.
• Manufacturing: QAD’s optimization engines reduce inventory carrying costs and highlight inefficiencies.
• Motorsports: NASCAR/PRIME uses AI to evaluate fuel strategies, risk scenarios, and competitive positioning.
• Consumer electronics: Sony uses AI platforms to enhance device experience and create deeper emotional connection, known as “Kando.”

Across these examples, ROI consistently shows up in four areas:

• Reduced manual effort and faster cycles
• Higher-quality decisions
• Lower operational risk and fewer errors
• Improved customer experience and conversion

In 2026, AI is no longer optional. It has become a competitive necessity, especially as Agentic AI lowers the cost and accelerates the pace of solving complex operational challenges that once required substantial human bandwidth.

Where Liberty Advisor Group Comes In

As organizations look to adopt Agentic AI, success starts with a strong foundation. That means modernizing legacy systems, ensuring clean and well-governed data, and implementing the infrastructure needed to support advanced, goal-driven automation.

Liberty Advisor Group specializes in helping enterprises build that foundation, modernizing platforms, improving data quality, and aligning systems so your organization is ready to unlock the full potential of AI.

If your goal is to move from exploration to execution with confidence, we can help you take the necessary steps to prepare your business for the AI-driven future.

If you’re a Technology Leader at your company or an Executive on your AWS journey and would like to talk more about driving technology-enabled value, reach out to Scott Albrecht or visit our website at AI Readiness & Value Creation to learn more.

About Liberty Advisor Group

Liberty Advisor Group is a goal-oriented, client-focused business and technology consulting firm based in Chicago. Since its inception in 2008, the firm has been committed to helping clients solve their most complex business issues, delivering tangible results that drive growth and reduce risk. Year after year, Liberty has been recognized for its people, culture, and hard work being  Certified™ by Great Place To Work in 2025.