AI roadmap

According to Accenture, companies that deploy AI at scale achieve ~3x higher return on AI investments than companies that are in the AI proof-of-concept phase. However, deploying AI at scale can be challenging for companies as it involves much more than implementing pre-built AI models for arbitrary business processes. 

Companies need to formulate an enterprise AI roadmap to accelerate and successfully scale AI adoption, Our solution to formulate the enterprise AI roadmap can be structured as:

1. Business strategy
AI is a powerful technology but implementing AI is not a goal in itself. An AI strategy must be developed to support a business strategy. Starting with defining the business strategy would help companies:

  • Review their business strategy to see whether it is still relevant,
  • Align their business strategy with the opportunities offered by AI,
  • Decide the processes where AI can add value and where alternative technologies can be used,
  • Ensure that the processes where AI can add value are ready for it,
  • Avoid unnecessary costs from failed AI projects that had been initiated without a concrete strategic roadmap

2. Data strategy
Data quality can make or break AI systems. Therefore, if you want to scale AI in your organization, your AI strategy must be supported by a solid data strategy. This includes:

  • Managing all components of the data lifecycle from collection and storage to integration and cleaning.
  • Ensuring that you feed your AI systems with high-quality data with accurate labels.
  • Automation is key to a scalable data strategy. You can manage data manually for a small AI model, but an enterprise AI strategy requires automated data pipelines.

3.Technology infrastructure
AI systems can be hungry for computing power. Therefore, it is important to have the infrastructure to develop and deploy AI models.

Cloud services can be a cheaper way to start with AI initiatives. However, an on-premise infrastructure with specialized hardware can be a more cost-saving option in the long run.

4. 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, this business units, called AI Centers of Excellence (AI CoE).

Companies should build AI CoEs with a broad range of skills, including AI and IT professionals as well as business executives and domain experts for specific use cases. This would help companies:

  • Bridge the gap between executive decision making and AI implementation,
  • Create a unified vision for AI across the enterprise,
  • Standardize common practices and facilitate communication.

5.Increase employee engagement
An organization-wide AI initiative cannot be limited to technology investments. You should also invest in the people aspect of your initiative and align the company culture and ways of working with your AI vision. This is because you will need new skills for a large-scale AI transformation. Moreover, employees may fear being replaced by AI which can slow down the transformation.

Feel free to contact our AI consultants, Consultants can help you speed up your enterprise AI roadmap and AI implementation.