Is There a Broken Salesforce Talent Pipeline? What Our 2025 Developer Survey Says

Two weeks ago, Salesforce Ben released our 2025 Developer Survey. We’re excited about this fresh look into the numbers behind what it means to be a developer in the Salesforce ecosystem. Among the most intriguing data were a set of numbers that serve as yet another data set that highlights a potentially ailing pipeline for young tech talent. 

This article sets out to answer the question: “Is there a broken Salesforce talent pipeline?”. And, if so, what does this mean for the future?

What the Talent Pipeline Looks Like

The top-level age demographics from the Salesforce developer survey show that only 4.2% of respondents fall into the 18-24 age bracket. This is not surprising considering that Salesforce is not a technology that is usually associated with secondary school or university curricula. We also know from our results that only 13% of responses state they came to the Salesforce ecosystem straight out of education. So let’s look at another facet. 

To understand the talent pipeline more clearly, it’s helpful to look at tenure in the ecosystem, that is, how many years someone has worked with Salesforce. Early-career professionals are the feeder for the experienced talent pipeline and the next generation of technical leadership. However, respondents with two or fewer years of Salesforce experience represent just 7.7% of the survey. Those with less than one year of experience account for only 2.9%, about a third of that group.

For a historical comparison, we can look back nine months to the Salesforce Ben Salary Survey. In that survey, 20% of developer respondents had 1–2 years of experience, and across all roles the figure was 14%. These numbers suggest that the proportion of respondents with two or fewer years in the ecosystem has declined by roughly 45-62%. We are currently compiling our 2025-26 Salary Survey, which will help confirm whether this trend is continuing. 

Zooming Out – The Broader Tech Outlook

Discussion of a looming talent crisis is not isolated to just Salesforce Developers or even the Salesforce ecosystem as a whole. In our own reporting earlier this year, Salesforce Ben shared about the 13% drop in employment for 22-25 year olds, with entry-level tech postings having decreased 67% since 2022. 

This is backed up by other data. The Stack Overflow Developer Survey has been a steady supply of data about the developer ecosystem at large. In 2022, the cohort of 18-24 year olds was 23%. Moving ahead to this year, it’s dropped to 14.2%, a decrease of 38%. Swinging the focus back to the Salesforce world, the 10k Advisors 2025 Talent Report further bolsters the case, showing the supply of developer talent slowing and a drop in demand for developer positions of 12%. 

The Impact of a Million Digital Interns

To understand why we’re experiencing these changes in the employment environment, there are two big factors potentially at play. One is the whiplash after the hiring boom of 2021. The other is the growing use of AI agents to perform previously rote and repetitive knowledge worker tasks, which used to be primarily reserved for entry-level workers. While each may play a role, increasingly the consensus is that the larger and more immediate factor is the rise in Agentic AI. 

In fact, this is not just happening in the technology sector. A WEF report from April this year cites risks across many entry-level positions. Anecdotally, a conversation with my own financial planner had him sharing how more and more the type of research work he used to delegate to entry-level team members is being handled by AI agents. Where once a new starter would be indoctrinated into their career as well as learn their trade by doing repetitive grunt work, AI agents have stepped in. 

So what’s to be done? 

A Way Forward for Developer Careers

The rise of “digital coworkers” raises a hard question: Is the tech industry trading long-term stability for short-term gains? Public companies find it hard to ignore the appeal of deploying millions of “digital workers” at a fraction of the cost of human employees. But the real price of this shift is still unclear.

Historically, major technological breakthroughs have increased both productivity and employment. Yet in this early phase of the AI cycle, we don’t know which tasks will drive future productivity or what new jobs will emerge. If generative AI follows past patterns, entry-level roles will still exist, but they may look very different from today’s.

There are, however, practical ideas for moving forward. A recent article from the Harvard Business Review lays out several courses of action employers can take: 

• Shift from rote tasks to higher-value work supported by AI, emphasizing judgment, collaboration, and creativity.
• Using humans as the critical evaluator of AI work.
• Redesign workflows so AI handles repetitive tasks while humans learn to ask better questions and frame more complex problems. 
• Focus early-career development on building talent, not assigning rote work.

Meri Williams, tech leader and former CTO of Pleo, addressed this problem recently at the Lead.dev conference. She noted that software engineering has historically benefited from repetitive entry-level tasks that help train new engineers. But there is less of that work to do. This shift will require a change in how junior developers acquire key skills and how soon they are given more responsibility. Earlier exposure to activities like code review and systems thinking may become essential. 

Summary

The super optimists envision a world without work. I’m not going to argue with that. But if you don’t subscribe to that, now is the time to invest time and energy in building the future workforce. 

This will require reversing the current trends that show a lack of investment in career starters. But doing so probably requires every industry to revisit what “entry-level” really means. Change is already underway, and further shifts seem inevitable. But what the future actually looks like will depend on whether we solve the entry-level career problem. 

Sources

• Human Learning about AI
• From tools to thieves: Measuring and understanding public perceptions of AI through crowdsourced metaphors (Hancock et al)
• ​​LinkedIn: AI eliminates entry-level jobs