Andy Parton, an AI marketing executive with experience at Diageo and BAT, has launched Destreza, an independent London consultancy focused on helping consumer businesses integrate artificial intelligence into brand strategy, marketing operations and execution.

Founded in May 2026, Destreza is built around what Parton describes as an “AI-Native Marketing Consulting” model. The consultancy targets marketing leaders and founders making decisions about AI operating models, brand development, internal capabilities and agency relationships.

The launch comes as generative AI moves from experimentation into broader marketing workflows. Tools based on large language models can now accelerate research, content development, creative ideation and analysis, but organizations still face questions about governance, quality, strategic differentiation and where human judgment should remain central.

Parton's career in AI marketing predates the current generative-AI boom. At Diageo, he led the 2019 launch of What's Your Whisky, an AI-powered whisky recommendation experience designed to help consumers navigate products according to taste. The company says the experience has since reached more than one million consumers worldwide.

That timeline is relevant to Destreza's positioning. Rather than treating AI as primarily a content-production technology, the consultancy is focused on applying it across the wider brand-building lifecycle, including consumer insight, strategy, creative development, activation, measurement and evaluation.

Before founding Destreza, Parton served as Global Head of Content at BAT, where his responsibilities included global brand building, premiumisation and AI-enabled marketing across the customer journey for three global brands.

The new consultancy is organized around its Destreza Operating Model, which combines specialist AI agents with a senior practitioner who remains accountable for strategic decisions and final recommendations. An Agentic Council is intended to review and refine outputs generated during the process.

In practical terms, the model separates high-volume analytical and production tasks from strategic accountability. AI agents can conduct research, develop campaign and brand strategies, support creative work, evaluate outputs and adapt recommendations for individual markets. Parton retains responsibility for diagnosing the business problem and deciding which recommendations should move forward.

That distinction reflects a larger issue confronting enterprise marketing teams: increasing access to AI does not necessarily translate into better marketing outcomes. As AI tools become widely available, differentiation may increasingly depend on the quality of an organization's data, strategic frameworks, governance processes and human decision-making.

“I want consumer businesses to come through the AI revolution with stronger brands, not just cheaper marketing,” Parton said.

Destreza initially plans to work with marketing leaders on AI operating models, brand strategy, organizational capability and agency configuration. Its consulting engagements are structured as Survey, a fixed-fee diagnostic; Shift, which addresses a defined business change end to end; and Focus, a longer-term senior partnership.

The company is also preparing to launch The Playbook for AI Brand Building in late September 2026. The ten-stage methodology is designed for founders and smaller marketing teams seeking a structured approach to building brands with AI.

The launch illustrates a broader evolution in AI marketing. Early enterprise adoption often centered on isolated applications such as automated content creation, personalization or campaign optimization. The next phase is increasingly concerned with redesigning the operating model itself: determining which activities should be automated, which should be augmented and which decisions require experienced human oversight.

For marketing organizations, that shift could prove more consequential than simply adding another AI tool to an existing technology stack.

Market Landscape

AI is increasingly becoming an operating-layer technology for marketing rather than a standalone content-generation capability. Platforms from Google, Microsoft, Salesforce and Adobe are incorporating AI into analytics, customer engagement, creative workflows and marketing operations, raising the competitive bar for organizations still treating AI as a series of disconnected experiments.

Destreza's model represents one response to that change: using multiple specialized AI agents for research and execution while placing a senior human practitioner at the center of strategic accountability.

The approach also reflects growing interest in agentic AI, where software agents can perform multi-step tasks rather than simply respond to individual prompts. The practical challenge for marketing leaders is establishing appropriate controls around accuracy, brand consistency, data use, intellectual property and approval processes.

Strategic Outlook

The significance of Destreza's launch is less about another AI marketing consultancy entering the market and more about the operating-model question behind it.

As AI capabilities become increasingly accessible, organizations may gain less competitive advantage from simply having access to AI tools. Instead, differentiation can shift toward how effectively businesses combine AI capabilities with proprietary knowledge, brand strategy, customer insight and human judgment.

For enterprise marketing teams, that means AI adoption increasingly intersects with organizational design. Decisions about internal capabilities, agency roles, workflows and governance could become as important as selecting individual AI platforms.

Top Insights

• Destreza applies AI across brand building, moving beyond content generation toward research, strategy, creative development and marketing evaluation for consumer businesses.
• Andy Parton's AI marketing experience predates generative AI's boom, including Diageo's 2019 AI-powered whisky selector, launched years before ChatGPT.
• The Destreza Operating Model combines AI agents with human accountability, keeping strategic diagnosis and final recommendations with a senior marketing practitioner.
• AI adoption is becoming an operating-model issue, forcing marketing leaders to reconsider agency structures, internal capabilities, workflows and governance.
• Agentic AI could reshape marketing execution, allowing specialized AI systems to handle multi-step research and production while humans retain strategic oversight.

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