Agile adoption: Evolving delivery with AI and platforms

Is Agile Dying, or Just Growing Up?

Every few years, the software world declares something “dead.” Waterfall died. Then microservices died. Now, it seems that Agile is being questioned in the same way. But if you look beyond the headlines, Agile is not dying. It is unbundling.

Teams are keeping the elements that drive outcomes and replacing the rest with practices that fit today’s delivery reality, such as platform engineering, DevOps, and AI-assisted workflows.

Agile adoption has diversified

The latest State of Agile report shows that Agile remains the dominant delivery mindset, but it increasingly appears in hybrid form alongside DevOps, product management, and compliance workflows. It adds that 71% of organizations use Agile in their software development life cycle, while 42% follow a hybrid model, a more common approach in larger organizations.

Meanwhile, DORA’s 2024 research defines what “good” looks like through four key metrics, including deployment frequency, lead time for changes, change failure rate, and time to restore service. It also identifies two trends shaping modern Agile, including:

The growth of platform engineering
The use of AI in the delivery toolchain

Agile remains the leading delivery approach, but how teams apply it is changing. Fewer follow it by the book. Instead, they adapt it to fit their size, risk, and architecture. With platform engineering and AI reshaping delivery, Agile is now judged by outcomes, not process.

Why teams feel like Agile is dying

Three main pressures are driving this perception.

Ceremony fatigue: Teams burdened by excessive meetings or “ticket theater” mistake rituals for agility. When overhead grows without improving results, frustration follows.
Scale and complexity: Large, regulated, multi-team programs rarely fit into a single framework. They require hybrid governance that combines iterative delivery with architectural planning, security, and compliance. Data shows that large organizations are increasingly hybrid.
AI and platform shifts: The rise of copilots, AIOps, and internal developer platforms has changed how work flows. Frameworks built for 2010s-era toolchains no longer fit today’s realities. DORA explicitly calls out AI’s growing impact and the evolving promise of platform engineering.

Outcome-driven agility replaces “Agile theater”

Forward-thinking organizations are converging on a few principles.

Outcomes over orthodox approach: Use DORA’s four key metrics as the scoreboard, not story points. If deployment frequency improves and failure rates decline, your version of Agile is working.
Lean governance for scalability: Retain iterative planning, but integrate lightweight architecture reviews, security gates, and privacy checks into the workflow. This hybrid model reflects how most enterprises operate today.
Platform thinking: Treat the developer experience as a product. Build paved-road CI/CD pipelines, provide self-service infrastructure, and focus on golden paths. Strong platform engineering practices correlate with higher delivery performance when priorities remain stable and user-focused.

Where does AI fit

AI has become a lightning rod in the “Agile is dead” debate. In truth, it is a force multiplier, but only for teams that already execute the fundamentals well. Here are some key areas:

At the keyboard: Controlled experiments show that developers complete tasks about 56% faster with copilots. The largest productivity gains occur in boilerplate, scaffolding, and exploration work.
Across the pipeline: AI now supports triage, incident prediction, and documentation summarization, which directly addresses the “waste removal” Agile always sought.

Nevertheless, productivity gains from generative AI are not guaranteed. They depend on context, task type, and team maturity. Leaders should pilot, measure, and scale carefully rather than apply blanket mandates. AI delivers the most value in teams with strong flow, testing, and CI/CD practices. Without that foundation, it can accelerate confusion instead of progress.

What it means for leaders

If Agile is evolving, leadership must evolve with it. The strongest organizations are demonstrating a few consistent patterns:

Re-anchor on outcomes: Publish the four key DORA metrics at both team and portfolio levels. Calibrate incentives around speed, stability, and quality rather than ceremony adherence.
Adopt hybrid on purpose: Clearly define your operating model. Specify what you retain from Scrum or Kanban, what you adopt from DevOps or SRE, and how architecture and security integrate into sprints.
Invest in platform and skills: Fund internal platforms, automation, and AI literacy. The biggest AI gains appear in teams that already have healthy delivery flow. Upskill teams to use AI responsibly and effectively.
Evolve the role of the PM and PO: Shift from backlog administration to outcome-based product management. Equip leaders to use data, AI insights, and user research to set stable priorities.

So, is Agile dying?

No. Agile is at the maturity it was always meant to achieve. It is just moving away from strict, rule-based interpretations and becoming more flexible and practical in how it’s applied.

The next wave of Agile is outcome-driven, platform-enabled, and AI-assisted. Teams still plan in small increments, learn continuously, and ship safely, but they now measure what matters and automate what does not.

If your Agile process feels broken, do not discard iteration and learning. Discard ceremony without outcomes. Build a hybrid model, connect it to DORA metrics, modernize your delivery platform, and equip teams to use AI responsibly.

At GenSpark, we see this evolution every day. Traditional Agile frameworks alone no longer close the gap. Our programs help organizations build hybrid delivery models that combine Agile fundamentals with AI adoption, DevOps maturity, and platform thinking, enabling teams to deliver faster and with stronger alignment to business outcomes.