AI&U Canvas — A Structured Approach to your AI Project

Once you have arrived at one or more business ideas for innovation with AI, it is a good practice to map out various parameters of that idea in a structured manner. This will make it easier to examine various aspects of the idea and the correlation between them. It serves as an excellent document for objectively discussing and refining the concept with other stakeholders. Below we have developed a method to do this, the “AI&U Canvas.” It is derived from the classic Business Canvas template, by Alex Osterwalder. Once filled out with the parameters of your business model for AI, the AI&U Canvas becomes your AI strategy blueprint. The AI&U Canvas consists of 8 fields defining the components of your AI solution. Three fields on the right (green) lists customer facing areas for the solution. Three fields on the left (blue) capture internal considerations for creating the solution. Two fields in the center (yellow) capture the value.

AI&U Canvas summarizes your AI strategy

These components are essential to understand any AI based solution. Here is the structure of a typical AI solution.

Anatomy of a typical AI solution

Every AI solution converts data from the real world — speech, sounds, images etc. — to value for the customer. An AI solution has interactions with (internal and/or external, one or more) customers, delivering business value. A satisfied and happy customer is characterized as one who benefits from the solution if the value provided meets or exceeds their needs. AI solutions typically can benefit from the support of certain AI services, like speech recognition, object recognition, or face recognition. These are basic AI services typically licensed from external companies. These services make it much easier and faster to build the AI solution delivering customer value. Often there is a collaborative need from other companies, called Ecosystem Partners, to make the entire solution to work. These are AI platform providers such as Google, Amazon, Microsoft, IBM, or specialized providers for Deep Learning. AI value add in the solution stems from the integration of AI. In the end the total solution must deliver overall business benefits for your business — in terms of you winning new customer, generating higher revenues, lower costs, or enabling expansion to other geographies.

These highlighted components (above) are identified and filled out in the AI&U Canvas fields providing an excellent documentation of the AI solution with all major components. It is recommended to fill out the fields in the order shown below as objectively as possible — possibly as a collaborative effort by the AI team.

You can download your copy of the canvas at the AI&U website

www.ai-u.org.

1. Customers and Stakeholders

Write down all customers (internal and external) served by the solution. You can also add their key needs.

Examples:

  • Internal customers
  • Stakeholders
  • External customer segments
  • End customers
  • Channel customers

2. Interactions

List the ways in which customer interact with the solution — especially where the AI elements come into play.

Examples:

  • Presentations
  • Sales process
  • Writing proposals
  • Customer service calls

3. Value Propositions

Specify the value your solution offers to each of your customer segments. Keep in mind that this is not a list of your solution features.

Examples:

  • Improve Ease of Use
  • Higher personalization
  • Proactive and responsive

4. Data Sources & Sensors

List all sources of data used for AI. If needed for the data, name the sensors. Remember that AI transforms data into value offered to customers, hence data is the raw material for AI.

Examples:

  • Medical history and clinical data for healthcare + sensors
  • Income, investments, expenses, etc. for tax consultants
  • Temperature, humidity, rain, soil, etc. for agriculture + sensors

5. AI Services

List AI services needed for the solution. These services are typically licensed from third parties. If known, name the provider.

Examples:

  • Speech recognition
  • Object recognition
  • Scene description

6. Ecosystem Partners

List all ecosystem partners needed for creation, operation and service of the solution.

Examples:

  • AI Platform — e.g. Google, IBM, Microsoft or Amazon
  • AI Neural-network set up, Deep Learning training and maintenance
  • Data sourcing

7. AI Value Add

Value added to the solution due to use of AI. This is an indicator of the incremental value that AI exclusively brings to your solution.

Examples:

  • Direct speech input — no typing
  • Automatic recognition of critical situations
  • Higher accuracy than a human expert

8. Business Benefits

Benefits for your business as a result of the solution. These are essentially benefits to your firm, with a financial and strategic impact, by offering an AI based solution.

Examples:

  • Reduction of human-power — lower cost
  • Higher customer satisfaction and trust
  • Higher quality of service — more competitive

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This article is written as part the AI&U™ (Artificial Intelligence & YOU) series by Sharad Gandhi and Christian Ehl. Watch for future articles on how to understand, learn, deploy and leverage AI for you and your organization. Our book AI&U was published in 2017. We also offer customer workshops to help companies jump-start in transforming their business with AI.

Contact us at www.ai-u.org

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