Every Business Needs an AI Strategy
To develop an AI strategy for your organization, there are six key components to consider:
Start with your business strategy: AI is a powerful technology, but its implementation should not be the end goal. The AI strategy should be developed to support a business strategy. This can help companies review their business strategy, align it with the opportunities offered by AI, decide where AI can add value (and where alternative technologies could be used), ensure readiness for AI implementation, and avoid unnecessary costs from failed AI projects.
Adopt a data strategy: Data quality can make or break AI systems. Therefore, an AI strategy should be supported by a solid data strategy, which includes managing all components of the data lifecycle from collection and storage to integration and cleaning. Ensuring that AI systems are fed with high-quality data with accurate labels is crucial. Automation is key to a scalable data strategy. Even if an organization does not have large amounts of data, it should focus on the quality of datasets. Small but high-quality datasets can produce better-performing models than large but low-quality datasets.
Ensure you have a reliable technology infrastructure: AI systems can be hungry for computing power. It is important to have the infrastructure to develop and deploy AI models. While cloud services can be a cheaper way to start with AI initiatives, an on-premise infrastructure with specialized hardware can be a more cost-saving option in the long run.
Establish a cross-functional center of excellence: A dedicated business unit that oversees and coordinates all AI initiatives in your organization is an important component of a successful enterprise AI strategy. This unit would identify AI use cases and set a roadmap for them. It should include a broad range of skills, including AI and IT professionals as well as business executives and domain experts for specific use cases.
Develop AI responsibly: As AI systems become more powerful and widespread, it is necessary to take a responsible approach to AI development. Business leaders and AI professionals must familiarize themselves with AI ethics and the principles of responsible AI development such as fairness, transparency, privacy, and security.
Increase employee engagement: An organization-wide AI initiative cannot be limited to technology investments. It is also necessary to invest in the people aspect of the initiative and align the company culture and ways of working with the AI vision. New skills will be needed for a large-scale AI transformation. Moreover, addressing employees' concerns about being replaced by AI is crucial to avoid slowing down the transformation.
