The Executive Brief
“Everyone talks about the weather, but nobody does anything about it.”
I love that quote from Mark Twain. Usually it makes me smile, but this week it didn’t. It made me think.
So many CEOs, CTOs, and CIOs ask me about AI. So many conversations, in fact, that I’m starting to wonder if the conversations make them think they’re getting things done. Maybe they rationalize it as collecting data or managing risk.
I’m all for due diligence, but not if it’s an excuse for inaction.
That’s why this week I wanted to write something that would help leaders move from talking to doing.
Btw, before you dive into it, here are the most interesting bits in technology from the last week.
The UK and US have signed a landmark deal to work together on testing advanced AI. The agreement signed on Monday says both countries will work together on developing "robust" methods for evaluating the safety of AI tools and the systems that underpin them.
This is the first such bilateral agreement. It’s modelled after a similar agreement for intelligence sharing between the two countries. We will have to wait to see if it produces anything useful.A large earthquake in Taiwan may have an impact on the chip supply chain. Some analysts are projecting that it may impact chip supply in Asia.
A Barclays analyst believes TSMC’s more advanced fabs could be affected for several weeks. It’s unclear how accurate this projection is but tech leaders should plan for some disruption.Microsoft and Quantinuum today announced a major breakthrough in quantum error correction. Using Quantinuum’s ion-trap hardware and Microsoft’s new qubit-virtualization system, the team was able to run more than 14,000 experiments without a single error.
While this is a single step forward in creating a commercially useful quantum computer, it bears watching. Much like AI, keeping pace with developments in this space will help tech leaders be prepared for when it starts to disrupt computing.
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5 Types of AI Adoption for CTOs
As each week brings rapid innovation in the AI space the pressure on CTOs to both enable and personally drive AI adoption & transformation in their business continues to significantly increase.
Clearly AI is here to stay and will most likely rapidly change Software Engineering organizations at a fundamental level, so it’s important for CTOs to learn how to approach AI adoption in the right way both for their own benefit and the benefit of their teams and colleagues across the company.
In this article we’ll look at the 5 most popular types of AI Adoption that most CTOs are being asked to get involved with.
5 Common/Popular Types of AI Adoption
Operationally within the technology organization
Embedded into the product suite
As a management tool for the CTO
For non-engineering departments like Marketing or Finance
For enhanced internal business intelligence
Now let’s look at each one.
AI Adopted Operationally within Technology Organizations
AI will transform every department & sub-department in a CTOs organization. This includes core Software Engineering, DevOps (CloudOps), Quality Assurance, Internal IT, Data Science and Cyber-Security. In fact, the transformation has already begun as of earlier this year. How you (as a CTO) bring in the right AI-based tools to move the needle in your department will be one of your biggest going forward. And the truth is this is quite difficult to pull off in the right way.
There are literally thousands of AI tools that in theory are supposed to help your team but setting them up in the right way and then tracking the before and after is a different ball game. As CTO this is an area you should expect to spend a lot of time on.
AI Embedded into the Product Suite
It’s fairly inevitable that no matter what kind of product or platform you’re supporting as CTO, AI will make its way into both how your product functions technically and the actual customer-facing features that are being offered. From LLM-based ChatBots to AI-driven Embedded Analytics to Natural Language Processing, AI is changing the front-end of products and will most likely end up taking over vital features and functionality over time. That means building new AI-based user experiences and finding clever ways to integrate them so it blends seamlessly with the “classic” parts of your product. Of course, you’re also going to use AI for backend functionality like search, automation, new machine learning models and so forth.
AI as a Management Tool for CTOs & Leaders
AI is quickly becoming a sort of “co-pilot” for CTOs. I’m increasingly seeing CTOs use it to help develop artifacts like roadmaps, technical requirements, and the spreadsheets they use to manage their work and teams. AI is also getting embedded into popular tools like JIRA. Learning about these tools and how they are made more effective with AI is a very useful skillset to develop as a CTO.
As AI continues to mature look for it to integrate into virtually every management tool in use today. The same goes for other leaders at the CTO level like CFOs, CHROs, CROs and so forth. You’ll have to end up with a favorite set of AI-driven management tools so best to get focused on discovering those as soon as possible.
AI for Non-Engineering Departments
Almost every CTO I talk to is under a great deal of pressure to bring in AI tools to help various departments in their business. This can range from AI tools for HR to Marketing to Finance. Leaders in non-technical departments are often relying heavily on the CTOs skills and expertise to understand which AI-driven tools will really make a difference for their organizations. And just like any new wave of technology, CTOs must stay apprised of the latest AI developments across a number of functional & departmental areas to really create value for their peers. It’s not enough to just know how AI will impact engineering. You have to read, research and test tools across a broad spectrum of functions and applicability.
AI for Enhanced Business Intelligence (BI)
AI really shines in the world of BI. In fact, AI has played a role in BI for years now, especially with the rise of Data Science. Lately however, a tremendous number of new tools have been released into the market and these more modern AI-driven capabilities are already having a big impact on BI value to the business.
Nowadays, CTOs are being asked to take over and run BI Teams from CFOs and COOs. As well, CTOs are being asked to get hyper-immersed into BI Teams and support them with both know-how and technology. What is clear is that AI-driven BI is going to be a big deal for years to come and CTOs are going to have get very conversant with the frameworks, tools, and technologies in this category.
Closing Thoughts
Right now, AI Adoption is reminding me a lot of where Cloud Adoption was in the early 2010s. It’s not a perfect analogy but there are some key similarities:
Cloud became part of the daily operations of tech teams, the same will happen with AI
Cloud became an integral part of products themselves, the same will happen with AI
Cloud became part of the tool-belt of CTOs with spend management tools, the same will happen with AI
Cloud became a part of non-technical departments as CFOs, CROs and other leaders adopted Cloud-based products and tools to help them run their organizations
Cloud became an integral part of BI Teams, with most modern BI tools and data living in the cloud, as well as cloud-providers offering native BI tools as part of their service
Of course, more ways to adopt AI will crop up as the industry learns how to use it best.