Techonology

Google GenAI experts weigh in on why companies are struggling for AI agents

Google is doubling down on artificial intelligence (AI) to drive revenue growth, according to Oliver Parker, vice president of global generative AI (GenAI) go-to-market at Google Cloud. Is.

Parker said during a recent interview in India that interest has been growing significantly over the past few months.

AI agents—autonomous systems capable of making decisions and taking actions—are designed to function with minimal human intervention. From driverless cars to smart home assistants and trading bots, these agents represent a significant evolution in AI technology.

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Google’s newly launched AgentSpace platform enables businesses to create AI-powered workflows that integrate seamlessly into operations, providing tools for tasks like enterprise search and data interaction. “This is taking AI beyond developers to the business level,” Parker said.

Over the past year, Google has poured resources into developing the agentic model. These systems can process extensive contextual data, predict multiple steps ahead, and execute tasks autonomously under human supervision. CEO Sundar Pichai outlined this change in a blog post announcing Gemini 2.0 in December, calling it the foundation of “the next era of models built for this agentic age.”

Building agentic systems in low-code environments is emerging as the fastest way to drive enterprise value.

When to use AI agents?

A December 20 blog post from tech company Anthropic states that the value of agentic systems lies in their ability to adjust latency and cost for better task execution, and that those using these systems should consider that this When does a tradeoff make sense?

However, companies need to deploy these systems judiciously, Parker said. “Think of a model as an engine and an agent as a car,” he explains, emphasizing that many enterprises embed large language models (LLMs) into workflows without creating fully autonomous systems.

For cost-sensitive and latency-critical use cases, Google offers Gemini Flash, a model optimized for speed and affordability. In contrast, the Gemini Pro accomplishes logic-intensive tasks, despite the higher cost and slower response time.

Parker cited a Southeast Asian chat assistant as an example of Gemini Flash’s usefulness, while Gemini Pro excels in scenarios requiring complex decision making.

Google’s AI strategy extends to Vertex AI, its enterprise developer platform that supports a variety of models. The partnerships with Anthropic, Foghere, Mistral and Meta’s Llama further underline Google’s commitment to flexibility, providing enterprises a suite of AI tools tailored to their needs.

Despite concerns about return on investment (ROI), enterprise adoption of AI is accelerating globally. Parker observed that while US enterprises focus on extracting value from business platforms, countries like India and China – traditionally developer-centric – are increasingly adopting higher-end services. “Building agentic systems in low-code environments is emerging as the fastest way to drive enterprise value,” he said.

Success stories like Apollo 24/7 Health’s AI-powered consultation assistant highlight the transformative potential of these solutions. These systems streamline processes and enhance the user experience while reducing costs.

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“Over the next 12-24 months, we’ll see advancements in models and platforms, with enterprise value moving beyond developers into packaged solutions like agent-based platforms,” ​​Parker said, citing AgentSpace’s seamless integration with tools like ServiceNow, Workday, and Will be transferred.” Sales force.

deal with increasing competition

However, there is increasing competition in the field of cloud infrastructure services in the region, including Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), and hosted private cloud services. According to Synergy Research Group, enterprise spending on cloud infrastructure services in the third quarter was $84 billion worldwide, up $15.7 billion or 23% from the third quarter of 2023, with generic AI a key factor behind the market boom. Is.

That said, Amazon maintains a strong lead with 31% market share, followed by Microsoft (20%) and Google (13%). According to Synergy Research, among tier two cloud providers, those with the highest year-over-year growth rates include Oracle, Huawei, Snowflake and Cloudflare.

Parker countered, “Google’s vertically integrated stack from silicon to infrastructure provides a unique advantage, allowing us to optimize for cost, latency, accuracy, and performance. This approach creates tailored solutions for different use cases. Enables, e.g., taking advantage of long context windows (up to 2M tokens in Flash)”.

According to Parker, Google hopes to drive a shift toward an AI-first tech stack, “which could redefine the hyperscaler (large cloud service providers) landscape as companies prioritize AI partnerships over traditional infrastructure”.

He said Google had “made significant improvements over the past year, reducing errors and increasing reliability”. For regulated environments, human oversight remains important. Tools like grounding with Google search increase accuracy, especially for currency and fact checking, “although no model is flawless yet”, Parker stressed.

As an employee, I use tools like our Gemini system every day, which demonstrates the importance of adopting advanced technologies.

Google is also supporting energy efficiency, he said — from water cooling data centers to optimizing tensor processing units (TPUs), “maintaining leadership in sustainability while meeting AI compute demands.”

ongoing learning

But what skills will employees need in this age of high automation?

“As an employee, I use tools like our Gemini system every day, which demonstrates the importance of adopting advanced technologies,” Parker said. He acknowledged that upskilling the workforce is important not just for the technical teams but across the board.

Parker also underlined the importance of multimodal AI, like the company’s Gemini model, which integrates text, speech, images and video. “More than 80% of recent meetings highlighted the growing demand for such capabilities, opening up new use cases and strengthening the role of AI in enhancing human productivity,” he said.

According to Parker, training is not just about building the AI ​​but also about using it effectively. He said, “For example, in 2023, we committed to train 1 million people over two years, but we have achieved this by leveraging platforms like YouTube and targeting diverse audiences—startups, traditional workers, and beyond.” That goal was achieved within months.”

Read this also Five artificial intelligence trends to keep an eye on in 2025

While acknowledging that the pace of change is challenging, Parker said Google is adapting by developing content faster and using its vast resources to deliver it. They concluded that education helps people see AI as an economic benefit rather than a threat to their skills.

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