Introducing Artificial Intelligence (AI) into a company’s processes can be a game-changer, but where should businesses start and what activities can yield the best results with the currently available AI technologies? Paolo Spreafico, Director Customer Engineering for Italy at Google Cloud, provides valuable insights on this topic.
According to Paolo Spreafico, the first step in effectively introducing AI into a company is to define a strategy that evaluates business needs and sets goals considering the tools and data available. AI can support a company’s digital transformation and business processes in various ways, from data analysis to automating repetitive tasks to creating new content through generative AI. However, it’s crucial for companies to consider enabling factors that allow AI to unleash its potential, such as utilizing data effectively.
Different organizations have varying levels of maturity and needs when it comes to AI adoption, so objectives and key performance indicators (KPIs) can vary significantly. Common areas for goals in AI adoption include increasing efficiency, improving decision-making processes, and optimizing resources. Companies with higher maturity levels may also aim to create new products or services and evolve their business processes.
“Selecting the right solutions to achieve these objectives plays a key role in the success of AI implementation”, says Paolo Spreafico. Google Cloud offers a wide range of solutions tailored to meet businesses’ needs in this area, such as Vertex AI, Google Cloud’s AI platform that allows for customizing AI technologies and generative AI models.
With the proliferation of AI applications within companies, understanding and mitigating potential risks related to security and privacy is crucial. Google takes data governance seriously and provides customers with the highest levels of security and control over their data stored in the cloud, including AI and generative AI products. When it comes to the necessary skills for introducing AI into business processes, there are strategic and technical competencies to consider. Google Cloud offers training courses and workshops to enhance individuals’ knowledge on topics related to the cloud, including generative AI, and provides tools like Duet AI to simplify the use of Google Cloud services for developers.
In terms of infrastructure, investing in a cloud-based infrastructure is typically the optimal choice for most AI use cases due to factors like cost containment, security, compliance, and ease of management supported by external expertise from cloud providers. Google Cloud, explains Paolo Spreafico, offers an optimized infrastructure for AI, including powerful accelerators like Cloud TPU v5p, designed to provide scalability and performance required for products serving billions of users.
