Cisco outlines enterprise approach to scaling AI adoption

Cisco has outlined how it has expanded the use of artificial intelligence across its business by focusing on trusted enterprise data, a secure internal AI platform and redesigned workflows. The company said these measures have helped it move beyond limited AI pilots towards widespread employee adoption.

The approach comes as many organisations continue to assess how to deploy AI across their operations. Cisco cited its 2025 AI Readiness Index, which found that only 33% of organisations had a formal plan to guide employees through AI adoption.

Trusted data

Cisco said the first step in scaling AI was improving access to enterprise data. The company said business information is often distributed across applications, data warehouses, documents and legacy systems, limiting the usefulness of AI tools.

Rather than concentrating solely on deploying additional AI models, Cisco said it invested in connecting enterprise data across existing business systems. It also worked to establish semantic relationships between datasets so AI systems could interpret information within the context of the wider business.

According to Cisco, this enables employees to obtain responses based on business information that is already available internally while maintaining appropriate access controls.

"AI is only as good as the data it can access," said Srini Namineni, Senior Vice President and Chief Automation Officer, Cisco Automation and AI Center.

Secure platform

Cisco said it also addressed the growing use of consumer AI tools by employees through the development of an internal platform known as Circuit.

The company said it recognised that employees were already experimenting with publicly available generative AI services. Rather than attempting to prevent that behaviour, it chose to provide a centrally managed alternative designed for enterprise use.

Cisco said Circuit provides employees with access to multiple AI models through a single platform. Users can connect AI tools to enterprise data, share prompts and projects, develop connectors and AI agents, and automate work without moving between separate applications.

The company said the platform was built around three design principles: security, usability and extensibility. Cisco said this approach aligned the platform with its responsible AI framework while allowing teams to develop reusable AI capabilities across the organisation.

"Those principles helped Circuit reach more than 100,000 users and 90% employee adoption. More importantly, it provided the foundation for a culture where employees built and shared capabilities of their own. We didn't get there through mandates or usage targets. We made AI secure, useful, and easy to experiment with – and adoption followed," said Namineni.

Cisco said widespread employee participation emerged through voluntary use rather than mandatory deployment, with the availability of enterprise-approved AI capabilities encouraging adoption across different business functions.

Workflow redesign

Cisco said scaling AI required redesigning business processes rather than simply inserting AI into existing workflows.

The company said many organisations focus on improving individual tasks with AI while leaving the broader workflow unchanged. Its approach instead involved reviewing processes from the beginning and identifying opportunities where AI could reshape the overall experience.

According to Cisco, employees now use AI to summarise information, analyse documents, search internal knowledge, generate content and automate routine activities.

The company said more than 21,000 software engineers use AI coding tools, with more than 80% using them each week. Cisco reported that engineers save an average of six hours per week through these tools, while employees across the wider business save an average of five hours each week.

Cisco said these productivity gains allow employees to spend less time searching for information or moving between systems and more time on decision-making and problem solving.

The company also identified agentic AI as the next stage of enterprise deployment. Cisco said AI systems that perform work on behalf of users require access to trusted data, enterprise context, governance controls and secure infrastructure.

Rather than aiming for complete automation, the company said organisations should determine the appropriate level of autonomy for each business task.

"Operationalizing AI is about creating the conditions for AI to become a trusted part of how the enterprise operates," said Namineni.