What we’re seeing

• The market numbers are strong. For example, the global market for AI in HR was valued at USD ~$8.16 billion in 2025 and is projected to reach ~USD 30.77 billion by 2034, with a CAGR of ~15.9%.

• In recruiting specifically, AI is already widely used: one study says ~89% of HR professionals whose org uses AI in recruiting say it saves time/increases efficiency.

• In terms of function and capability: AI is no longer just “nice to have” for HR—according to Gartner, Gen-AI adoption in HR jumped from 19% in June 2023 to 61% by January 2025.

• The kinds of tools: AI in HR/Recruiting is being deployed for resume screening, candidate matching, chatbot-based initial interviews, predictive analytics for attrition/retention, onboarding automation, etc. 

So all signs point to a transformative wave of digital tools automating parts of the HR/tracking/talent space, and platforms that embed those tools becoming more valuable.

 Why that transformation matters

From your point of view as a senior web/mobile dev, someone working in automation, dashboards, data → here’s why this trend is especially worth noting:

1. Efficiency & scale
   Automation brings huge scale: tasks that used to be manual (screening 1000 resumes, scheduling interviews, tracking candidate flows) are now increasingly handled by AI-powered platforms. That opens up new architecture and UI/UX problems to solve (how to integrate AI agents, how human + machine workflows coexist).

2. Data + predictive insight
   HR tech is turning into a data business: not just “post job, get applications” but “predict which candidates will succeed, where skills gaps are, how retention will trend”. That means developers and data people are needed to build frameworks, dashboards, and pipelines for talent intelligence.

3. Platform and ecosystem opportunity
   Because the market is growing fast and valuations are strong (investors are backing niche HR/Recruiting AI companies), there’s space for new entrants, integration layers, niche tools (e.g., skill-matching engines, bias detection, candidate experience optimisation). For someone like you with varied tech skills (cloud, APIs, automation), that’s relevant.

4. UX + human-machine collaboration
   One of the key shifts is the interplay of humans + AI: HR teams must move from doing everything manually to designing workflows where AI handles repetitive tasks and humans handle the nuanced, human-centric ones. For developers and product teams, this means designing systems where the “machine part” is obvious, transparent, and trustworthy, especially in something as sensitive as hiring. 

But it’s not all smooth sailing.

As with any rapid shift, there are important caveats and risks worth being aware of, as they highlight areas where you can add value or where things might go off course.

• Ethical, fairness, and trust issues: When AI is used in hiring, concerns around bias, transparency, candidate perception, and fairness become critical. If a system filters resumes or interviews candidates with minimal human oversight, how do we know it’s fair? 

• Tech maturity and integration challenges: Some organisations adopt tools, but the full suite (data, process, culture) may not be ready. For example, just plugging in an AI screening tool doesn’t fix poorly defined hiring workflows. As one report notes, many organisations are not yet well prepared for the impact of AI in recruiting.

• Human+machine balance: There’s a risk of automation overshooting. While many tasks can be automated, human judgment, cultural fit, and team dynamics remain hard to codify. That means platforms need to enable humans, rather than entirely replace them.

• Valuation versus real value: High valuations signal investor excitement, but they also raise the question—are all parts of this business going to deliver sustainable value, or will there be consolidation, failures of models? Growth is strong, but execution matters.

 What this could mean for you

Given your expertise (web/mobile dev, API work, automation, dashboard/data), here are some concrete reflections:

• If you’re exploring side-projects or startups, a niche HR/Recruiting tool is a viable area: e.g., developing integrations that pull hiring data into dashboards, building predictive analytics for talent acquisition, or creating better UX for candidate matching.

• In your work with dashboards/reporting (you mentioned working with state health dashboards, etc), the “talent intelligence” side of HR tech could borrow similar patterns—large data, pipeline visualisation, KPI tracking — and you could apply your skills there.

• From a product architecture viewpoint, these systems require robust pipelines (data ingestion from ATS/CRM, AI screening module, human review workflow, feedback loops). Your background in API development and automation is relevant.

• Because the space is moving quickly, staying current on the tech stack (for example, how generative AI is being used in recruiting, how candidate-matching algorithms are evolving) is useful; you might anticipate where companies will invest.

• If you are advising organisations (like you do in consulting contexts), you could help frame how they adopt HR tech: not just “we’ll buy a tool” but “how do we redesign our hiring workflow, train our HR team, integrate with our IT landscape, ensure fairness and data governance”.

 My bottom line

Yes—it absolutely signals a transformation: the speed, scale, and investment show that the industry of recruiting/HR is being re-imagined through digital tools and automation. But it’s not a magic bullet. For it to be truly effective, organisations must pair the technology with new workflows, human-centric design, ethical frameworks, and smart integration.

For you, as someone who bridges tech, automation, and strategic systems, this is a ripe area. The transformation isn’t just about “someone pressing a button and hiring happens,”  it’s about building platforms, designing workflows, and enabling humans and machines to work together in smarter ways.