When most companies talk about AI, they focus on chatbots or content generation. But for forward-thinking organizations, AI is becoming more than a tool. It’s infrastructure.
OpenAI’s recent report, AI in the Enterprise, shows how global leaders are using enterprise AI solutions to scale operations, reduce costs, and create new business value.
If you’re a mid-sized company looking to go beyond experimentation, these lessons offer a practical path forward.
See how Ticomix supports custom AI development for business operations
AI Is Becoming a Core Business Layer
The companies highlighted in OpenAI’s report, such as Morgan Stanley, BBVA, Mercado Libre, and others, are not using AI for surface-level tasks. They are embedding it directly into customer service, software development, compliance, and internal operations.
Across all examples, one idea stood out: AI works best when the people closest to the problem are part of the solution.
7 Key Enterprise AI Strategies That Any Business Can Learn From:
- Evaluate before rolling out
- Who did it well: Morgan Stanley
- The solution: To ensure quality and build trust, Morgan Stanley ran structured evaluations (evals) to measure just how well AI models performed on key tasks compared to benchmarks. Now in production, 98% of Morgan Stanley advisors use Open AI every day.
- Why it matters: Evals reduce risk, uncover weaknesses early, and make it easier to win stakeholder support.
- Learn more: Using AI solutions with financial services
- Empower experts with custom AI tools
- Who did it well: BBVA
- The solution: BBVA rolled out ChatGPT Enterprise across the organization, enabling employees to build over 2,900 custom GPTs in five months. Teams across credit risk, legal, and customer support created their own solutions without waiting for IT.
- Why it matters: The best AI use cases often come from the people doing the work, with the most intimate knowledge of their pain points. With the right guardrails, non-technical users can build powerful tools.
According to OpenAI, the deep research tool saves an average of four hours per complex task. Learn how your team can benefit from deep research for business using AI.
- Set ambitious automation goals
- Who did it well: OpenAI
- The solution: OpenAI’s own support teams built internal AI platforms on top their Gmail to automate ticket creation, update records, and manage email workflows.
- Why it matters: The biggest value often comes from replacing manual tasks with AI that can take real action, not just provide suggestions.
See how Ticomix helps businesses automate workflows with custom AI-powered applications.
- Fine-tune AI for your business needs
- Who did it well: Lowe’s
- The solution: Lowe’s used fine-tuned GPT models to improve product tagging accuracy by 20% and error detection by 60%. These improvements addressed challenges with inconsistent product data across thousands of suppliers.
- Why it matters: Fine-tuning lets AI understand your specific language, brand, and context. The result is more accurate and relevant output.
Read our guide on how to harness AI for your business and turn tailored models into competitive advantage.
- Build AI infrastructure for developers
- Who did it well: Mercado Libre
- The solution: Mercado Libre created an internal AI platform using GPT-4o and GPT-4o mini called Verdi to help its 17,000 developers quickly build AI-powered apps using natural language and built-in security protocols.
- Why it matters: By giving developers better tools, companies can build more consistent, secure, and scalable AI applications.
- Tip: Ask whether your development environment supports fast and secure AI integration.
- Start early to maximize ROI
- Who did it well: Klarna
- The solution: Klarna launched an AI customer service assistant that now handles two-thirds of all support chats. Response times dropped from 11 minutes to 2. Meanwhile, 90% of Klarna employees use AI tools daily.
- Why it matters: Starting early creates momentum. Teams get familiar with the tools, use cases improve, and the business compounds its learning.
Ask how Ticomix can help you launch a low-risk pilot to explore AI use cases in your business.
Think bigger than productivity
These companies are not just using AI to write emails or summarize content. They are:
- Automating reviews and tagging at scale
- Generating customized product content
- Replacing manual research with AI-powered synthesis
- Taking real action inside systems and workflows
This is where the future of enterprise AI is headed. It is not assistive, it is operational.
How Ticomix Builds Real-World Enterprise AI Solutions
At Ticomix, we help companies turn AI from a buzzword into business value. Whether your goal is process automation, legacy system integration, or intelligent search, we bring the technical expertise and strategic thinking to make it work.
We partner with your team to:
- Identify high-impact opportunities
- Run pilot projects and evals
- Build and deploy custom AI tools
- Integrate with your existing software and data systems