Companies across industries are increasingly recognizing the potential of AI to revolutionize their businesses, create new products and services, and gain a competitive advantage. However, no two companies are the same and navigating the complexities of AI adoption can be difficult. Here are five essential steps companies can take to successfully integrate AI into their operations by 2024 and unlock its transformative potential.
Consider the AI hype: Focus on business needs and objectives… and whether or not AI can deliver results today.
Experimenting is great, but only with a purpose. Before you dive headfirst into the world of AI, it’s critical that you ask yourself, “What challenges does my business face? What opportunities can AI address?” For example, your goal may be to improve customer experience, streamline internal processes or optimize decision-making.
Clearly defined goals provide a roadmap for your AI journey. It also helps you avoid the tempting pitfall of adopting AI for its own sake. Focus on specific needs and align your AI initiatives with your overall business strategy.
Also keep in mind that AI is still in its early stages: it can’t do everything we hope for today. It is imperative to gain a good understanding of AI’s capabilities in advance, compared to your goals, to avoid investing in something that is ultimately not yet possible.
Chief Architect and AI Officer, Solace.
Quality and quantity: build a data-driven foundation
The quality and accessibility of your data directly impacts the effectiveness and accuracy of your AI models. This is where robust data governance practices and integration solutions come into play. Data silos are the enemy of AI. They prevent AI from learning, evolving, and providing meaningful and valuable insights for your business. Breaking silos requires organizations to prioritize data governance practices and data integration solutions. Another important aspect is implementing tools that provide clean, consistent, and readily available data for your AI applications. Quality data is the fuel behind high-quality AI.
Embrace true real-time technology
Traditional data architectures often struggle to keep pace with the real-time demands of AI. That’s why it’s essential to embrace event mesh technology, a proven approach to distributed networking that enables real-time data sharing and processing. By leveraging event-driven architecture (EDA), companies are unlocking a new realm of real-time AI that allows them to quickly respond to events, trigger automated actions, and make decisions based on the latest information.
This approach to AI helps companies deliver more personalized experiences, such as real-time recommendations, offers and support based on individual needs. It can also enable predictive maintenance, where problems or failures are anticipated in advance to allocate the right resources to the right place at the right time. Having EDA as the central nervous system for your data not only allows AI to work in real time, but also makes adding new AI agents significantly easier.
Develop your custom AI platform
Developing AI applications can be slow, hampering their potential value. Platform engineering can act as a much-needed accelerator. This emerging trend aims to modernize enterprise software delivery, especially for digital transformation. Furthermore, it optimizes the developer experience and accelerates the delivery of customer value by product teams. With these platforms, developers can gain access to automated IT infrastructure management, pre-configured tools and pre-built components, allowing them to focus on what really matters: building innovative AI solutions faster.
The overarching focus is on streamlining infrastructure, automating tasks and providing ready-to-use components for developers. However, such applications will only be hypothetical if they cannot be designed and developed in the first place. Therefore, it is important and promising to note that Gartner sees Platform Engineering reaching maturity in 2024.
Break the chains of legacy systems
Amid the rush to real-time and AI-driven operations, large, diverse organizations will still be limited in their ability to realize optimal business value due to their reliance on a complex mix of legacy and/or siled systems. Last year, IDC found that only 12% of organizations connect customer data from different departments.
The AI data flow will lead to a greater industry-wide need for event-driven integration, but only with an enterprise architecture pattern will new and old systems be able to work together. Without this, you can’t deliver seamless, real-time digital experiences, connecting events across departments, locations, on-premise systems, IoT devices, in a cloud or even multi-cloud environment.
AI adoption should not chase the latest trends, but focus on making strategic investments that deliver tangible business value. By prioritizing your business and following the steps above, you can unlock the transformative potential of AI and propel your business forward in the data-driven era. Remember, AI is a powerful tool, but its success depends on careful planning, strategic implementation and a clear understanding of your business objectives.
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