AI's value  is not in the technology, but in how it  is used. Although  AI integration may seem to  be an extension  of current  integration philosophies, it offers new challenges. 

The challenge can be best illustrated with  the  example of a personal AI Agent that helps simplify  your  life.  Unlike the  internet where you must  navigate to each site individually, the AI Agent will bring all those capabilities together. 

For example, you  have to make a big payment on your credit card, but your  debit account has insufficient funds.  Your assistant could assist in transferring  money, coordinating the  payment, and optimizing any benefits.  It can take into account all other financial transactions and your financial goals. All without input  from  you  (explainable AI will  tell you  precisely  all that happened).  To accomplish  this an integration of  AI Agents will need to occur.  You personal AI  Agent  will talk to your bank's AI  Agent and coordinate with  the credit card AI Agent. It  may  also  integrate with  other AI Agents (financial institutions, government, etc.). 

These  integrations  aren't simple.  They  require  a trust model where  credentials  can flow between Bots  (ATLaaS, BAaas).  The AI  Agents require  very  sensitive  information, that the butler Agent can't compromise (or even  see).

The  simplification of  services  that AI Agent integration offer is new and  revolutionary.  It removes transaction friction at light speed.  Just think  of how  optimizing government  services across agencies  could save  money  and time.  This expands to include  every  business  transaction.   Every  participant Agent has  the  requirement to  facilitate transactions  and protect their clients.

The example has the consumer at the center.  It offers a new view of the consumer owns their  relationships.  AI Agents however do not need  a human  consumer.  They  can be triggered by  other stimuli (complex events).  These are the manager Agents  that are supervising worker Agents (infrastructure monitoring).  It will take a vigorous governance model to manage this sophisticated, integrated Agent ecosystem.

The Right Strategy is focused on very instance where technology  is used.  It is focused on a tool designed for an outcome.  

The proper use of AI and the  foundation of the  Right Strategy are essentially  the same - it is all about  Context.

Assisted AI is where the AI is not integrated into the user experience, but is a separate instance where the consumer can prompt on related topics.  A consumer may use multiple AI assistants.  These Agents would be trained differently  and help resolve different types of issues.  

The context depends on the consumer.  It is not based on what the consumer is doing.

Augmented AI is where the Right Strategy intersects AI integration.  AI becomes another capability that is integrated in the tool.  

The context (right time, right consumer) drives every  integration with  AI  in the tool.  It passes credentials to the AI.  The AI can now be very precise models (small language  models, transactional models) trained on the  most sensitive  internal information. 

An Agent is  a Right Strategy tool in that it  integrates capabilities  to get an outcome(s).   Just like any  other tool, its success  is  dependent on understanding context.

The third usage pattern is automated AI.  This is where  AI has integrated consumers.  It is either  implemented as an independent Agent  (event  driven like infrastructure monitoring) or used as a capability in an automated process (can this piece of work be resolved  without intervention).

A mature AI empowered enterprise will use  all three consumption models.

One of the biggest impacts of AI (so far) is in coding.  It is  a game changer for  developers and  enterprises.  

What AI can do with code and code management is just the  beginning. 

In the  Right Strategy, AI can be used to write, improve,  and optimize tools.  Tool construction was always  about  empowering the business to configure their solutions.  Just like with  code, AI can assist this  construction.  AI can monitor tools success.  It can look for capabilities that can be integrated to improve outcomes.  It can monitor and optimize usage.  AI  can transparently  move work from an augmented pattern to an  automated pattern.

The combination of AI and the  Right  Strategy (tool  building, context, credentialing) can easily  achieve  digital success.