TMTPOST— The rise of AI Agents is the headline story of 2025. Yet, despite the buzz, the industry faces a sobering reality: large models have landed, but they have yet to fully take root.
On the surface, 2025 has been branded the “Year of the Agent.” Viral consumer platforms like Manus and a flood of AI Agent showcases at this year’s World Artificial Intelligence Conference (WAIC) have propelled Agents to the forefront of public and industry attention.
While consumer-facing applications continue to capture imaginations, enterprise-grade Agents—designed to address real business needs and drive revenue—are inching closer to commercial reality. The flourishing popularity of Agents reflects the broader maturation of large model applications.
However, behind the scenes, many enterprises remain bogged down in the complexities of implementation. High infrastructure costs, entrenched data silos, and elusive business value have left many companies navigating through a frosted glass, where flashy exhibition demos obscure the messy realities of day-to-day operations. Much-anticipated disruptive applications are languishing in prolonged proof-of-concept stages, awaiting a more pragmatic route to scalability.
“No enterprise wants to flip a coin and gamble on uncertain outcomes,” said Zhang Xin, Vice President of Volcano Engine, in a recent interview with TMTPOST. “What businesses need is a clear path to converting their industry expertise into tangible productivity gains through large models.”
Despite these hurdles, the market is undeniably heating up. In 2024, there were 570 contract-winning projects linked to intelligent agent platforms, with disclosed contract values totaling 2.352 billion yuan. The first half of 2025 has already seen 371 project wins—3.5 times the volume of the same period last year, and nearly two-thirds of 2024’s total, with demand expected to surge further in the second half.
Volcano Engine, a subsidiary of ByteDance, has emerged as a dominant player. Since the second half of 2024, it has consistently topped the charts in both contract value and volume, thanks to its full-stack intelligent agent platform, HiAgent. According to Chen Xi, Head of HiAgent, success in enterprise AI demands far more than just a strong model; it requires a tightly integrated solution blending technical tooling, business adaptation, security, services, and proven best practices.
“Having a great model doesn’t automatically translate to great applications,” Zhang said. “The missing link is robust engineering practices—prompt design, orchestration, privacy controls, system integration—all wrapped into a development platform like HiAgent.”
Volcano Engine’s approach reflects a broader industry shift. In the early days, companies focused heavily on improving LLM capabilities, believing better models would naturally lead to better applications. However, as Zhang noted, the realization has set in that models are just one piece of a complex puzzle. The real challenge lies in building scalable platforms that can convert model potential into business-ready solutions.
