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    Home » Sections » AI and machine learning » Are you really ready for AI?

    Are you really ready for AI?

    Promoted | Before you throw caution to the wind, it’s important to consider whether your business is actually ready for AI.
    By Calybre9 October 2024
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    Are you really ready for AI? CalybreArtificial intelligence seems to be the topic on everyone’s lips. The pressure to join the movement is extreme, but before you throw caution to the wind, it’s important to consider whether your business is actually ready for AI.

    The reality of AI

    While some may dismiss AI as mere hype, it is evident that it is more than that. Recent market analyses show that 65% of organisations are already using AI (McKinsey report) and since 2023, the global adoption of AI has surged by an impressive 72%.

    While AI stocks have seen fluctuations and some hyperscalers have experienced stock price drops, the overall trend points towards increased adoption and integration of AI technologies in mainstream business operations.

    A practical approach to AI readiness

    Navigating the daunting journey to AI readiness is like planning a holiday: there is a fair amount of planning required to make the most of the experience, from choosing your destination and must-do activities, to getting all of your travel documentation in order.

    Step 1: Know your use case (choose your destination)

    The first and most crucial step in your AI journey is identifying a specific business problem or opportunity where AI can create significant impact. Instead of looking for a use case to prove AI, start with a clear understanding of your business challenges and evaluate if using AI is the best solution.

    Common AI solutions include fraud detection, risk assessment, financial forecasting and regulatory compliance. In human resources, AI can assist with talent acquisition, while operations departments can benefit from supply chain optimisation and predictive maintenance.

    Always ask the question, “Why not use AI to solve this problem?”, followed by, “What value will it provide?”

    Step 2: Evaluate your readiness (plan the trip)

    Assessing your organisation’s readiness for AI involves examining four key building blocks:

    • Ensure your AI initiative aligns with strategic goals and provides clear business value.
    • Evaluate the quality, quantity and accessibility of your data, as this will be crucial for AI success.
    • Determine if you have the necessary expertise in-house or need to acquire it, considering both technical and business skills.
    • Assess whether your current technology stack can support AI workloads.

    Identifying your maturity or readiness in each of these areas will expose the gaps you need to fill to start the journey.

    Step 3: Choose the AI model (choose your means of travel)

    Selecting an appropriate AI model is crucial to solving the business problem.

    AI models fall into two main categories: preexisting models and custom models. Preexisting models are already trained and ready for use, such as ChatGPT or image recognition systems. Custom models, on the other hand, are built for specific, niche purposes and trained on your unique data. The type of model you choose depends on your use case.

    For example, demand forecasting might require a regression model, while recruitment could benefit from a classification model. Regulatory compliance might leverage generative AI with retrieval-augmented generation (RAG), and identification tasks often use computer vision models.

    Understanding the different types of models and their applications will help you make an informed decision for your specific needs.

    Step 4: Consider legislation and governance (your travel documents)

    As you embark on your AI journey, consider local regulations like the EU AI Act, Popia and GDPR to ensure compliance. These acts focus on the responsible use of data and AI, covering themes such as fairness, transparency, safe-guarding and accountability.

    You might be tempted into spending less effort on the application of data governance – the exciting, leading-edge AI solution is, after all, the ultimate goal. A strong focus on defining the processes, policies and tooling required for data governance will, however, result in a more robust and quality output.

    Step 5: Building your AI team (your companions and travel guide)

    People are the main ingredient when enabling AI and solving business problems. Frequently, though, a variety of different skills are required that don’t all come packaged in a single person. Plan for ongoing skills development and investment in AI literacy programmes to ensure that your employees are empowered to deliver with new technologies.

    Partnering with specialised consultants to ensure that you have the diverse skills required may be necessary to meet your goals and reduce your risk. External partnerships can accelerate the AI journey by providing expertise in translating business needs into AI strategy, offering industry-specific insights and ensuring compliance with legislative and governance issues.

    Key capabilities to look for include technical skills in data architecture, data and AI, as well as the ability to train and enable the wider organisation.

    Conclusion

    By following a structured approach to AI readiness, organisations can position themselves to harness the power of AI effectively. The journey to AI readiness is ongoing, requiring continuous learning, adaptation and a willingness to embrace change. Whether you’re just starting out or looking to expand your AI initiatives, the key is to begin with a clear understanding of your goals, assess your readiness honestly and build a strong foundation for success. Are you ready to take the next step in your AI journey? The future is AI-enabled, and the time to prepare is now.

    Calybre is a data consulting company based in South Africa and the UK. To find out more about how Calybre can help you on your AI journey, visit us at www.calybre.global.

    • Read more articles by Calybre on TechCentral
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