The 2024 Gartner CIO and Technology Executive Survey found that 81% of respondents believe that building, developing or customizing digital technologies for the business area should be the responsibility of IT departments (led by CIOs). Only 15% of CIOs believe that this responsibility should be shared equally with business areas, according to the survey.1

The ultimate responsibility for building, developing or customizing this software, whether within the CIO organization or in lines of business, falls to software engineering leaders. These leaders are in a key position to enable their organization to become builders of software, because they are at the intersection of business and technical domains, between strategy and implementation. But, to do so, they must build a world-class software engineering organization. 

In this podcast, we explore the role of software engineers and developers as AI and generative AI are infused into their future. Gartner expert analysts discuss a few of the many layers of this complex topic in the following areas:

• Reality versus hype — The quest of business and IT leaders separating out what is reality versus hype in order to be pragmatic. More specifically, software engineering leaders must ensure they stay grounded on what is reality so they can prioritize and start piloting and experimenting.
• Value and measurement — All leaders need to be able to track and measure things so they can determine what they want to put in production, scale and make part of their long-term approach. Above and beyond that, they need to be able to quantify the value. 
• Skills and talent — This involves a deeper understanding of the value of software engineering expertise, performance and productivity.
• Trends and the future — As always, it is important for leaders to stay abreast of what is coming and how to prepare for it.

To address these important focus areas, we discuss several important concepts in the podcast. A few are highlighted below.

Reframe the ROI Conversation

The current ROI conversation is focused on cost reduction. Gartner experts are focused on guiding leaders to value generation. It is important to stop thinking of AI as cost-reduction mechanisms or a tool that could help reduce headcount. Instead, it’s important to focus on AI and GenAI as force multipliers that enhance developer experience to such an extent that they enable activities that deliver real business value. 

Amplification Fallacy

There is an idea that generative AI will “amplify” people’s skills. However, if you carefully think about the concept — “amplifying” something just makes it louder, it doesn’t make it better or higher quality. As such, it is important to identify and investigate the differentiated impact across the software development life cycle and specific developer skills. 

Some initial findings show that GenAI provides a bit more of a productivity boost for junior developers. However, there is also countervailing data that less experienced developers overtrust the outputs of GenAI and are thus more error prone and more likely to introduce security vulnerabilities. 

For more senior developers, the starting point is that they have the expertise to know what good looks like, as they already have deep knowledge of a problem space, of architectural standards, of best practices and experiential knowledge. Hence, if they are open to using new tools, experimentation and tinkering, they are the ones who can quickly iterate and figure out the best ways to prompt and interact with GenAI coding assistants.

Augmentation Versus Agency

One of the most critical and foundational concepts for the success of AI is trust — engendering trust for both the creators and consumers of the solutions. Software engineers are among the creators of the solutions. The spectrum of increasing trust begins with a low trust level where augmentation rules the day. As trust increases, more tasks are offloaded but not entire roles. Imagine an AI assistant in a craftsman’s workshop. As we arrive at a level of trust where we can offload roles, think of the full apprentice or journeyman. With increasing reliability comes increasing trust, and with increasing trust we transition from “tool-based extension” (augmentation) to “social extension” (we recognize AI as having agency).

Two of the many predictions Gartner analysts have published on this topic and we explore in the podcast are:

• By 2028, 75% of enterprise software engineers will use AI coding assistants, up from less than 10% in early 2023.
• By 2028, systematic adoption of AI coding assistants in 2023 will result in at least 36% compounded developer productivity growth.

Evidence

1 2024 Gartner CIO and Technology Executive Survey. This survey was conducted online from 2 May through 27 June 2023 to help CIOs determine how to distribute digital leadership across the enterprise and to identify technology adoption and functional performance trends. Ninety-seven percent of respondents led an information technology function. In total, 2,457 CIOs and technology executives participated, with representation from all geographies, revenue bands and industry sectors (public and private).

Disclaimer: The results of this survey do not represent global findings or the market as a whole, but reflect the sentiments of the respondents and companies surveyed.

Our host Frances Karamouzis is joined by Arun Batchu and Phillip Walsh, who are both expert analysts in Gartner’s software engineering leaders team. Batchu is a vice president, and he helps software engineering leaders build their software design, development and people strategies. Walsh is a senior principal analyst who helps software engineering leaders develop and implement strategies to build a world-class software engineering organization.