Democratized, operationalized, responsible: The 3 keys to successful AI and ML outcomes
Artificial intelligence (AI) and machine learning (ML) have become buzzwords in the world of technology, and for good reason. The potential of these technologies to drive innovation and increase competitive advantage cannot be overstated. Many organizations are now investing in AI and ML to streamline processes, automate tasks, and create new products and services. According to Gartner, the AI and ML market is predicted to reach $134.8 billion by 2025. Similarly, IDC forecasts that investments in AI and ML will jump from $85.3 billion in 2021 to $204 billion in 2025, resulting in a CAGR of 24.5% for the 2021-2025 period.
The benefits of AI and ML are clear, but success is not guaranteed. To achieve successful outcomes, organizations must focus on three strategic pillars: data, algorithms, and infrastructure. The first pillar, data, is crucial as the quality and quantity of data will directly impact the success of your AI and ML initiatives. It is important to have high-quality data that is easily accessible and secure. The second pillar, algorithms, refers to the mathematical models that process data to deliver insights and predictions. Developing effective algorithms requires expertise in data science and machine learning. The final pillar, infrastructure, is the foundation that supports your AI and ML initiatives. It includes the hardware, software, and cloud services needed to deploy and manage your AI and ML applications.
To succeed with AI and ML, it is essential to have a clear strategy that focuses on these three pillars. This eBook provides practical recommendations for developing your strategy and achieving successful outcomes. It includes insights from experts in the field and real-world examples of organizations that have successfully implemented AI and ML initiatives.
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