Building a future-proof AI strategy means balancing innovation and agility with control and visibility. Given the pace at which AI adoption is progressing, and how fast AI is still evolving, this can feel like a pretty daunting task at times. That’s why Tyk is here to help. Our new ebook – AI, APIs and AI readiness – which you can download for free, provides a practical blueprint for long-term success.
To give you a taster of how the ebook can help, we’ve pulled out some key points around continuous learning, secure integration, agile governance, and the strategic use of AI agents in the article below. You can use these five top takeaways to start building a future-proof AI strategy, then dive into the ebook for deeper insights.
Why future-proofing matters in the AI era
AI is here, and it’s here to stay. It is transforming businesses and reshaping industries. As such, strategizing around how to implement, govern and scale AI within your enterprise is no longer optional; it’s part of ensuring your business model is future proof. Let’s look at five lessons you need to embrace as part of your AI strategy in order to achieve this.
Lesson 1: Innovation needs strong governance
When you think about innovating, strong governance might not be the first thing that comes to mind. However, as we considered recently in relation to API governance, the right approach can actually support creativity and agility, rather than stifle it.
Governance provides the framework that means you meet your security and compliance obligations in a robust and standardized way. Working within your governance framework, therefore, means your teams don’t need to worry about the technicalities of implementing authentication (for example). Instead, they are free to create and innovate without worrying that they’re going to break the business or incur the wrath of your regulators. They have the headspace to do what they do best, while you have the peace of mind that comes with knowing your AI – and your APIs – are governed in a way that meets your security and compliance needs.
Lesson 2: Success starts with leadership and collaboration
Your technical team might have run a successful AI proof of concept (PoC), but moving seamlessly from PoC to production will require strong leadership buy-in and collaboration across the business. Your AI strategy needs to account for this.
AI can – and likely will – make a fundamental difference to how your enterprise operates. As with any major change or strategic shift, the way you lead AI implementation is pivotal to its success. Leaders who are committed to setting the vision for AI, allocating resources and driving change will be those most likely to see their AI initiatives succeed.
Lesson 3: AI is only as good as your data (and people)
Trash in, trash out. It’s widely accepted that if you don’t manage the data that’s feeding your LLM with appropriate care, your AI output will suffer as a result. This means you’ll need a clear and comprehensive approach to data management, covering both the data itself and the individuals in charge of it. The return on your AI investment depends on it.
Without a sound approach to your data (and the people who manage it), you’re likely to face inconsistent and unreliable model outputs. These have the potential to impact productivity, meaning time is lost to troubleshooting, damage your reputation with customers and land you on the wrong side of your regulators. All of which can be major distractions from the pursuit of your business goals.
Lesson 4: API management is a strategic enabler
The way you manage your APIs is critical to your AI success. Your APIs are a key enabler of AI integration, underpinning machine-to-machine communication, AI-driven service creation and automated provisioning and access.
You can use API management to implement security policies that keep your data safe and ensure robust access control. Implementing observability can also provide the visibility you need for more informed decision-making and a smoother compliance journey.
Lesson 5: Be ready to adapt – continuously
AI continues to evolve at a staggering pace, showing no signs of slowing down as businesses race to adopt it. Gartner tells us that by 2026, more than 80% of enterprises will have used generative AI APIs or models, or deployed GenAI-enabled applications in production environments. In 2023, that figure stood at under 5%.
The race for adoption is not just about what AI can do today but also about keeping pace with its evolution. This means enterprises need to implement AI in a way that means they can continue to flex and adapt as technology develops – which is where the AI value chain comes in, supporting robust security and operational efficiency at the same time as flexibility.
How Tyk supports long-term scalability and innovation
With long-term scalability in mind, Tyk has developed a purpose-built platform for accelerating innovation without sacrificing control. Tyk AI Studio supports successful and strategic enterprise AI adoption with centralized management, an AI gateway, AI portal and secure, collaborative chat interface.
From the AI, APIs and AI readiness ebook, which serves as a full AI readiness blueprint, to enterprise-grade governance with Tyk AI Studio, we’ve provided all you need to lay the foundations for future AI success. Why not talk to our expert team to find out more?
