With many organisations still only in Stage 1 of their AI journey, where isolated deployments of discrete AI technologies reign, and who would be happy to get to stage 3, where a unified data strategy and more sophisticated AI usage is in play, the potential for AI to dramatically enhance both predictive and generative AI is clear and leads to stage 4 and 5 – but how do you get there, and what truly are the benefits?

AI is here, there and everywhere, and rapidly advancing. Your company’s use of AI needs to evolve and mature, as does your own personal AI needs.  It may well be the case that you and your company don’t yet know all the benefits that AI can deliver.

The same goes for the software and hardware platforms your business deploys and operates on, with those software and hardware vendors very attuned to the need to continuously improve their solutions so their customers – and your customers – can reap the benefits of enhanced capabilities, cost savings and more.

When it comes to deploying AI solutions within your business, there are levels of understanding and operation that all businesses are at, whether it is yet to meaningfully deploy any AI solutions at all, right through to mastery of the AI mindset and integration with your business models to ensure that you are at the top of your game. This is while keeping a keen eye on AI’s rapid advancements, so you know when to deploy the inevitable AI upgrades that are to come.

So, while the development of AI is in a constant state of improvement, there are systems you can use to gauge where you are on your company’s AI journey. Certinia’s Pragmatic AI Maturity Model lays out a five-stage taxonomy for understanding a company’s current readiness to deploy AI, and what you and your company need to succeed with more advanced AI use cases.

It’s also worth noting that Certinia’s Director of Product Marketing Greg Smith, who is a dedicated proponent of the Pragmatic AI Maturity Model’s 5 stages, notes that there are perhaps only 20 companies worldwide at Stage 5.

This week Greg will speak at Singapore’s SuperAI event on the topic “Are You AI Ready”, June 5-6 2024, with more on the conference here.

So, what is Pragmatic AI? What are the five stages? Why are only 20 or so companies at Stage 5? And why is this important for your business?

There are two video interviews to watch in addition to the one with Greg Smith below. The first is with Certinia’s Global Analytics Evangelist, Joe Thomas, who also explains pragmatic AI and how AI can also stand for “augmented insight”, and my interview with Dan Brown on how Certinia takes AI to the next level with its US Spring 2024 release! is here

Ok, here is video interview with Greg Smith immediately below, in full, after which you can read Greg’s breakdown of the five stages for yourself, so please watch, and read on!

Here are each of the five stages, as Greg Smith explains:

Stage 1: Initial
 
At this stage, AI technologies are used in a scattered and uncoordinated manner. The data environment is disorganised, with fragmented data and systems heavily dependent on spreadsheets and isolated tools. Operational data is not well-organized to support AI effectively. Most organisations find themselves at this starting point today.
 
Stage 2: Repeatable
 
Stage two is characterised by productised deployments of AI, where standalone solutions have AI integrated into them. Organisations start implementing more cohesive data practices but still struggle to connect all operational data. The focus is on structuring data to begin leveraging more advanced AI tools and technologies.

 
Stage 3: Controlled
 
At this stage, organisations have successfully implemented a cohesive data strategy, consolidating both transactional and operational data into a unified system. This comprehensive data integration allows for cross-departmental analysis. Organisations can now utilise AI for more advanced functions, such as conducting basic predictive analytics.

 
Stage 4: Optimised
 
In this phase, organisations have established sophisticated data infrastructures that enable the use of advanced AI models for intricate predictions and insights. AI is fully embedded in core business operations, enhancing decision-making and efficiency. Reaching this stage typically requires years of dedicated effort in data management and AI implementation.
 
Stage 5: Continuous Improvement
 
Organisations in this final stage achieve an optimal state where they operate a closed-loop system with pristine, real-time data that perpetually enhances AI models. AI-driven predictions are not only actionable but also continuously evolve through feedback from implemented actions, fostering an ongoing cycle of improvement. There are likely fewer than 20 organisations globally that are at this stage today.
 
Here is a summary of the topics I spoke about with Greg Smith:

– I started by introducing Greg, and asked him to give us a refresher of a quick recap of the Certinia story in 2024.

– Greg explained what Certinia’s Pragmatic AI Maturity Model is, in brief, and what is pragmatic AI, before we went into the details.

– We then delved into Greg’s five-stage taxonomy for understanding a company’s current readiness to deploy AI, and what is needed to advance up the ladder to succeed with more advanced AI use cases.

– We went through each stage one by one.

– Greg then shared a sneak peek of his SuperAI talk, dubbed “Are you AI Ready”.

– After this Greg shared the biggest questions businesses ask him and Certinia about implementing AI.

– Greg shared his Australian trip thus far, and what else we need to know about Certinia and AI.

– We then finished with my three final questions – memories of Greg’s first computer, great advice he has received in life, and his final message to the viewers and readers.

So, please watch the video interview with Greg Smith above to learn more!