AI agents at scale: Enterprise essentials you need to get right

Greetings Cohere Community,

This month, we deepened our mission to put secure, private AI in every enterprise by announcing new strategic partnerships with Dell Technologies and SAP. Together, we’ll bring the smartest, most efficient, agentic AI platform and models to the highly regulated sectors that Dell and SAP serve, helping customers to quickly scale AI agents throughout their workforce.

“Enterprise adoption requires more than powerful models; it demands trust, scale, and real-world applicability. That is why SAP is excited to announce our expanded partnership with Cohere, a leader in secure, enterprise-grade AI.” – SAP News Center

We’re entering a new phase of enterprise AI adoption — one where companies can choose to harness agentic AI and become truly AI-empowered organizations, or risk being left behind. The real question now is how fast enterprises can grasp the opportunity, scale advanced AI, and rethink the nature of work. 

Racing towards secure, agentic AI 

AI first movers are already outperforming their peers, a gap that is set to widen as more productivity gains from the technology kick in. According to Microsoft’s 2025 Work Trend Index, there’s a new breed of company: the “frontier firm” that scales rapidly, powered by dynamic AI insights and teams of humans collaborating with AI agents.

“An AI-first company is built around AI from the ground up. It rethinks its entire operational model, replacing traditional workflows with AI-powered decision-making and execution. Where traditional businesses use AI as a tool, AI-first companies treat it as the foundation.” – Jehan Hamedi, Founder and CEO, Vizit

Rather than treating AI as a simple add-on to existing workflows, workers are looking to  orchestrate and collaborate with agents to run entire business processes and automations. According to the survey, 81% of leaders expect AI agents to be integrated into their company’s core workflows in the next 12-18 months. Building enterprise AI agents is now the top imperative for businesses. 

How to lead the AI charge

From our work with leading companies, we believe there are three levers that matter most for fast enterprise AI adoption: security, efficiency, and customization.

Security: Navigating AI in regulated environments

Strong security isn’t just a nice-to-have for AI deployment — it’s an essential foundation for accelerating adoption. That’s particularly the case in complex, regulated industries, where adoption is being held up by concern over data privacy and compliance issues. Some 39% of bank executives, for instance, say that security and data privacy concerns are dragging on the pace of deployment.

“Anytime you go through an application, you first have to solve for legal and compliance. It’s got to meet our security and risk and controls, and then it's customer experience.” – Darrin Alves, CIO of infrastructure platforms, JPMorgan Chase

Adopting enterprise-grade AI enables companies to insulate themselves from the growing risk of “shadow AI,” where employees share sensitive work information with publicly available models without their employers’ knowledge. Using private deployment, potentially as part of a hybrid solution with cloud-based architecture, can give organizations peace of mind over sensitive data together with the flexibility to scale AI in response to demand and manage costs.

Secure AI takes on added importance in the context of agentic AI. Before integrating these powerful agents into their systems, businesses need clear guardrails, rigorous evaluation, and fallback mechanisms to ensure they behave predictably under pressure. 

Efficiency: The enterprise AI superpower 

Until recently, better AI was widely seen as synonymous with bigger AI, requiring ever larger amounts of compute power. That narrative is now shifting decisively. 

“Everybody wants to use the Ferrari, but if you’re just going down the street, you might just need a bike.” – Monica Caldas, CIO, Liberty Mutual

According to one recent report, the inference cost (the expense of running a trained model) for a system performing at the level of ChatGPT-3.5 dropped 280-fold in the two years following its release in November 2022. 

“With these efficiency gains, any business can run AI to increase productivity for employees with AI agents that can automate work.” – Nick Frosst, Co-Founder, Cohere

Our Command A model, for example, only requires two GPU chips compared to 32 for competing models. This leap in cost-effectiveness will allow enterprises to better leverage private deployments — crucial for highly regulated industries — and to scale agentic systems efficiently.

Customization: Your unique AI value proposition 

To maximize the value and competitive advantage of AI, enterprises need it to truly understand their business, including their unique terminology, workflows, and regulatory concerns. The answer is customization.

Recent data shows that 75% of organizations investing in generative AI are prioritizing model customization. High-performing companies are nearly twice as likely to adapt or fine-tune foundation models, unlocking gains in efficiency, accuracy, and risk reduction.

“We have domain know-how — we understand our industries. And we have the data. Together with AI, this is a winning combination.” – Roland Busch, CEO, Siemens AG 

Training models on company data unlocks new capabilities like personalized AI assistants, strengthens core functions through agentic workflows, and boosts productivity by streamlining repetitive tasks.

Cohere, for instance, partnered with Fujitsu to custom-build its Takane model, training it on Japanese business language and on complex technical concepts across the specialized, regulated industries that the company serves.

Taking the bold leaps

The window for decisive action is short. Frontier firms’ advantages will compound as they automate more processes, deploy more AI agents, and unlock new productivity from their workforces. Get started with lean, easily governed models, like Command A, customizing them with your proprietary data, and try North, our agentic AI workspace that lets you build and deploy custom AI agents all within your security perimeter. It’s never been easier to launch secure, agentic AI for businesses.

For more, catch up on our latest articles, or read on for this month’s highlights and upcoming events.

Product 

This month, we announced two new partnerships with Dell and SAP to bring agentic AI to businesses worldwide. Our vertically integrated AI platform North enables us to deliver fully customized solutions that give customers complete control of the product experience. 

For Business

Many of our leading customers are redefining the future of knowledge work. Take DraftWise, powered by our suite of models, Command, Embed, and Rerank on Microsoft Azure AI Foundry. It automates the most tedious tasks for lawyers and delivers accurate information for even the most complex use cases.

Developers

Command A, our state-of-the-art generative model, is now the highest-scoring generalist LLM on the Bird Bench leaderboard for SQL, outperforming other systems that rely on extensive scaffolding to tackle these SQL benchmarks. Command A delivers these results out-of-the-box, underscoring its incredibly strong performance.

Research

Cohere Labs launched the Aya Vision Technical Report, addressing the complexities of integrating multimodal capabilities into multilingual models. Watch the video overview. 

Company

Our CEO and Co-Founder Aidan Gomez spoke at the B7 Summit in Ottawa, chaired by the Canadian Chamber of Commerce, to discuss the future of AI and innovation. As a Canadian leader in the industry, Aidan emphasized the importance of adoption across the economy and government for competitiveness.

Upcoming events with Cohere 

• June 11 [Online]: Join Cohere Head of Security Prutha Parikh and AI Safety Product Manager Diane Chang discussing the key considerations for secure AI adoption. 

For all upcoming events, explore cohere.com/events or watch our past events on-demand.

Spotlight

• AI meets finance: From strategy to impact. Watch the latest webinar featuring Cohere experts Robin Gainer, Nicolás Morales, Laura Moss discussing how financial institutions can win with AI. 

• AI reasoning and the future of decision-making. AI reasoning models can handle more complex tasks and improve decision-making processes. Learn how to address their limitations and ensure ethical, transparent, and reliable AI systems. By Jay Alammar and Edward Kim

• What’s holding back government AI, and how to move forward. Explore how governments can overcome AI adoption challenges, including ethical concerns, data privacy, and the need for robust regulatory frameworks. By A.J. Bhadelia, Paul Lawrence, Sohail Manoussi, and John Weatherly