You’ve organized groups and committees to get your collective corporate head around the potential of AI. Great. Maybe you’ve even ring-fenced some funds for your exciting new AI venture. Even better. But this is where many enterprises stumble. How do you get from the theory of harnessing the power of AI to the reality of doing so in a secure and well-governed manner?
This is where the following seven steps come in. They take you from wanting to make the most of AI to actually doing so. If you want to level up the AI readiness of your enterprise, you’re in the right place.
Step 1: Sort your API governance out
No, it’s not a typo – we said “API” governance intentionally there. Because if you want to govern your AI successfully, you need to start by governing your APIs. It is your APIs that feed data into your LLM, so that’s where you need to introduce consistency, security and trust. Proper oversight of your APIs will reduce the risk of everything from AI data leaks and security breaches to ethical concerns.
Focus on access control, monitoring and auditing, versioning and standardization across your API ecosystem. Then, with your API governance sorted in terms of compliance, security and visibility, successful AI governance will follow suit.
Step 2: Understand your AI costs and controls
Don’t let your AI costs spiral. You can take control from the outset by forecasting everything related to your AI, from infrastructure and training your model to maintaining it and recruiting a suitably talented team.
You’ll also need a tool to control your costs as your AI usage progresses. Tyk AI Studio is an excellent choice, enabling you to use your AI gateway to control everything from expenses to accountability, enforcing smarter budgets. You can also monitor the return on investment (ROI) of your AI initiatives to assess their cost-effectiveness.
Step 3: Develop a robust data strategy to enable your AI to thrive
The quality, security and accessibility of your data are key to the success of your AI initiatives, so you’ll need a robust data strategy. Start by identifying your data sources and ensuring your infrastructure is sufficient to collect data at scale, with appropriate validation in place to assure its accuracy. Be sure to comply with regional regulatory requirements in relation to data processing and privacy.
Step 4: Build a cross-functional AI team, not a silo
If you want your AI to thrive, it can’t just sit with one team. You’ll need buy-in from across the business, creating alignment not just on the technical details but on the business goals and value of your implementation.
Creating a cross-functional AI team is a great approach. In addition to your AI experts (data scientists, machine learning engineers, researchers and so on), you’ll need engagement from your C-suite execs, operational teams and legal and compliance staff. With clear roles and responsibilities defined, you can ensure cohesive decision-making that aligns with the direction of the business, while slotting your AI initiatives into operational workflows.
Step 5: Implement ethical AI practices
Ethical considerations are an essential part of any AI implementation. You’ll need to mitigate bias, ensure fairness, provide transparency into AI decision-making and define accountability, all while ensuring you comply with data and privacy regulations. And once you’ve put your ethical framework in place, you’ll need a program of continuous monitoring and auditing to ensure it remains effective over time.
Step 6: Prepare for AI scalability
This is another key area where Tyk AI Studio has your back. By centralizing your AI management, it enables you to unify and control AI usage across your enterprise, even as you scale at pace. The AI gateway enables you to seamlessly connect to AI tools and models, delivering secure, scalable access to AI services across teams. The AI portal empowers your developers with a curated AI service catalog, with the tools they need to innovate and build faster, all backed by intuitive chat interfaces for direct interaction with AI tools and data sources.
Having your AI gateway as a single point of control means you can scale while maintaining control. You can ensure compliance with global privacy regulations through customizable data flow management and track usage statistics, cost breakdowns and tool utilization to optimize resources. Everything you need for your AI initiatives to flourish as you accelerate your business growth.
Step 7: Foster a culture of AI adoption
AI requires a cultural shift, not just a technical implementation – and that means engaging your people. All of them. You’ll need to empower your teams to understand the benefits of AI if you want them to embrace it. Like any major business shift, clear communication is an essential part of a smooth transition.
To foster an effective culture of AI adoption, you’ll need to invest in training your teams on AI tools (something you should have budgeted for in step 2 above!) and roll out a data literacy program, ensuring everyone understands how to leverage the business value of your AI models. Having AI advocates in teams across the business can help. You should be able to lean on the cross-functional AI team you created in step 4 to take on this role.
From AI readiness to AI reality
Ensuring your enterprise has the right foundations in place can deliver the readiness you need to be at the forefront of the AI revolution. Add Tyk AI Studio into the mix and you have a powerful opportunity to excel at your fingertips. Get a demo of Tyk AI Studio today to discover how to build smarter and scale faster.
