Industry executives and experts share their predictions for 2026. Read them in this 18th annual VMblog.com series exclusive.
By Marcelo Tamassia, Chief Technology Officer, Syntax
Generative artificial intelligence (GenAI) is entering a pivotal new phase in 2026: the scale-up era. The past year was marked by experimentation, as enterprises concentrated on proof-of-concept pilots and limited deployments. But in 2026, the challenge shifts dramatically.
Organizations must move beyond prototypes and take on the harder, more consequential task of operationalizing GenAI at enterprise scale – building durable, secure, and enterprise-grade capabilities that deliver measurable business value, integrate seamlessly with existing systems, and withstand real-world demands.
Preparing for the Next Wave of GenAI
From my work with customers across industries, I’ve seen that the most successful and scalable GenAI initiatives don’t succeed by technology alone. They are anchored in 10 core components that shape long-term success:
1. Data: GenAI is only as powerful as the data behind it. Enterprises must invest in robust foundations for grounding and context injection. Equally critical is ensuring data quality, accessibility, and domain relevance to enable faster, more accurate AI-driven decision making.
2. Technology Stack: Instead of stitching together disparate tools, organizations need an integrated infrastructure for deploying, running, and scaling GenAI. This includes compute, storage, APIs, vector databases, and developer platforms. A cohesive stack improves reliability, governance, and security – while reducing latency and cost.
3. GenAI Orchestration: As GenAI moves from single-model outputs to multi-step, agent-driven processes, orchestration will become the backbone of enterprise AI. Orchestration frameworks must support agent development, model chaining, and complex workflows – complete with governance, routing logic, monitoring telemetry, and prompt management.
4. Tooling & Integrations: In 2026, enterprises will expect agents not just to generate outputs but to take meaningful actions such as retrieving data, triggering workflows, and driving business processes. An effective integration layer seamlessly connects GenAI with enterprise systems, APIs, and tools to make this possible.
5. Model Strategy: Choosing the right model – whether open-source, proprietary, fine-tuned reasoning vs. non-reasoning, or API-based – is key to each use case. Equally important is maintaining the flexibility to switch models as needs evolve, balancing performance, cost, compliance, and control.
6. Memory & Context Management: Raw data alone isn’t enough; contextual grounding unlocks GenAI’s full value. This means enriching models in real time with internal data, user input, business logic, and advanced techniques like Retrieval-Augmented Generation (RAG).
7. Change Management: Technology only delivers impact when people adopt it. Enterprises must drive trust, adoption, and empowerment across teams with structured programs that include training, enablement, and continuous feedback loops to sustain engagement.
8. Governance and Compliance: Scaling GenAI safely requires strong guardrails and oversight. Organizations must establish clear usage policies, ethical standards, and auditability frameworks to address data privacy, IP rights, hallucination risks, and model behavior.
9. Executive Alignment: C-suite sponsorship is the single biggest determinant of success. In 2026, leaders must link GenAI programs to strategic vision, ROI, KPIs, and cross-functional priorities-while securing budgets and sustaining momentum against competing demands.
10. People and Ownership: Scaling GenAI requires dedicated ownership across business, product, and technical domains. Enterprises must define roles for executive sponsors, product owners, prompt engineers, and data stewards to ensure accountability and sustained progress.
In the year ahead, these components will not remain static; they will evolve, interconnect, and demand greater sophistication. The organizations that adapt and elevate each one will distinguish themselves – moving beyond experimentation toward enduring, enterprise-wide impact.
Setting Up for Success in the New Year
2026 will be the inflection point: the year when GenAI either becomes deeply embedded into the enterprise operating model or stalls as a collection of pilots that never scale. The difference will come down to strategy and execution. Companies that design their approach around these 10 components won’t just capture occasional wins – they will establish a sustained competitive advantage, positioning GenAI as a core driver of growth, efficiency, and innovation.
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ABOUT THE AUTHOR
Marcelo Tamassia, Syntax’s Global Chief Technology Officer since 2019, drives the company’s technology and innovation strategies. With over two decades in technology, Marcelo emphasizes empowering individuals to provide exceptional solutions. He holds advanced certifications from AWS, Oracle, and Microsoft, along with an MBA from the University of Florida and postgraduate education from Stanford University, underscoring his commitment to continuous learning and excellence.
