AI Agents for Business: How To Automate Workflows and Cut Costs

2. How is ADK different from a closed AI product? 

Using a closed AI product is similar to using an editing application such as CapCut: you can use the features provided, but you cannot redesign the underlying product. ADK is different because it gives developers an open framework for creating their own agent applications and defining how those agents behave, communicate, and use tools. Most existing AI agents work the same way: useful within the limits they were built for, but closed to modification. This is a key consideration for any business evaluating how modern development tools and approaches fit into their workflow. 

Google’s ADK changes that. With this, developers can inspect, modify, and extend the agent’s behaviour at the code level. You are no longer limited to out-of-the-box functionality. If you need an agent to do something slightly different, or something entirely new, you can build it. That opens the door to agents genuinely tailored to the way your business operates, rather than agents you have to work around. 

3. Why is standardisation important in AI agent development? 

Standardisation eliminates fragmentation, allowing agents to be built once and deployed repeatedly across different systems without rebuilding from scratch each time. 

Without a shared standard, every development team builds agents differently. The result is fragmentation: time wasted, work duplicated, and agents that cannot talk to one another or be reused in different contexts. 

Google’s ADK introduces a common structure so that agents can be built once and deployed repeatedly. A specialist agent trained to summarise transcripts, for example, can be plugged into any system that needs that capability, without rebuilding it from scratch each time. This is what makes agent networks scalable. It is also what makes them maintainable as your needs evolve. 

4. What is multi-agent architecture and how does it work? 

Multi-agent architecture is a system where multiple specialist AI agents work together in a pipeline, each handling one clearly defined task, to complete complex workflows more efficiently and cost-effectively than a single large model. 

The best way to understand it is through a concrete example. Imagine your business receives hundreds of inbound enquiries every week, by phone, email, and web form, in different languages and at all hours. Processing all of that through a single, advanced AI model would be expensive and inefficient. ADK enables a smarter approach: a pipeline of specialist agents, each with one clearly defined job. 

The result is an automated pipeline that handles the full journey from raw enquiry to routed action and significantly reduces manual triage while retaining human review or approval for sensitive, unusual or high-value enquiries. Each agent does only what it is trained to do, which keeps the system fast, predictable, and cost-effective. 

5. Can AI agents reduce operational costs? 

A carefully designed agent system can reduce operational costs by matching each task with the appropriate model, tool or workflow. 

 Using the most capable AI model for every routine task can be inefficient. A straightforward process such as classifying an enquiry may not require the same level of reasoning as analysing a complex technical brief. With ADK, developers can assign different models and tools to different agents based on the requirements of each task. 

Specialist agents bring the same discipline to AI costs that good hiring brings to staffing. A lightweight summarisation agent can process 200 call transcripts for pennies. Sending those same transcripts to a top-tier model could cost hundreds of pounds. The saving is not marginal; it is structural.  

For more on how AI-driven automation can save your business thousands of hours, see our practical breakdown. 

 The scale of this issue is real. Salesforce CEO Marc Benioff recently revealed on the All-In podcast that his company expects to spend around $300 million on Anthropic tokens this year, primarily on coding work. Tellingly, he added that not every token needs a frontier model, calling for an intermediary layer that routes simpler tasks to cheaper models, exactly the discipline a well-designed multi-agent architecture builds in from the start. Meanwhile, AI usage keeps climbing: Similarweb found that AI platforms generated over 1.13 billion referral visits to the world's top 1,000 websites in June 2025, up 357% year-on-year, a measure of how quickly AI is becoming a mainstream channel between businesses and their customers. At that kind of volume, unmanaged spending on routine tasks becomes impossible to justify. 

Token efficiency matters too. Every word sent to an AI model costs money, including pleasantries. Saying please and thank you to an AI adds tokens to every prompt and, across millions of users, this behaviour has been estimated to cost AI providers millions annually. Well-designed agent prompts are concise and directive by default, and ADK’s architecture enforces that discipline at the system level. 

6. How are businesses using Google ADK right now? 

Businesses are using Google ADK to build production-ready multi-agent pipelines that automate enquiry handling, internal routing, and workflow management at a fraction of the cost of traditional approaches. 

At Cardiff App Developers, we are not just watching this development from the sidelines. Our operations team is actively building a multi-agent pipeline using ADK right now, with a specific focus on automating inbound enquiry handling: summarisation, categorisation, and intelligent routing. You can read more about our approach to AI development and integration. 

The goal is to reduce the manual overhead of processing high volumes of inbound contact, route genuine opportunities to the right people faster, and do it at a cost that makes sense for the business. Our development team is currently building and testing a multi-agent workflow using ADK, focused on the summarisation, categorisation and routing of inbound enquiries. 

That means we can design and deploy these systems for client organisations too. Whether you are looking to automate enquiry handling, streamline an internal process, or build a bespoke agent for a specific business function, we have the technical capability and the practical experience to deliver it. If you are weighing up your options, our guide on how to choose the right app development partner is a good place to start. 

The businesses that move first on this will not simply save time and money. They will build operational advantages that are genuinely difficult for slower-moving competitors to close. Automated pipelines running around the clock, processing enquiries and routing opportunities without human overhead, compound over time. For founders and CTOs weighing where to invest their technology budget, multi-agent automation is one of the clearest cases for near-term return on investment available right now. 

If you are interested in exploring how AI agents can automate your business processes, get in touch with our team to discuss your requirements. 

Frequently Asked Questions About Google ADK 

What is Google ADK? 

Google ADK (Agent Development Kit) is a framework developed by Google that allows organisations and developers to build, deploy, and manage AI agents using a standardised architecture. It is open source and supports multiple programming languages including Python, TypeScript, Go, Java, and Kotlin. 

What are AI agents? 

AI agents are autonomous software systems capable of completing tasks, making decisions, and interacting with other systems with minimal human intervention. Unlike a standard AI chat tool, agents can act, run processes, and pass outputs to other agents. 

What is a multi-agent system? 

A multi-agent system consists of multiple specialised AI agents working together to complete complex workflows efficiently. Each agent handles one specific job, such as summarising, categorising, or routing information, making the overall system faster and more cost-effective than using a single large model. 

Can small businesses use AI agents? 

Yes. AI agents can automate repetitive tasks such as enquiry routing, summarisation, customer support, and reporting, making them accessible to organisations of all sizes. You do not need a large in-house technology team to benefit; a development partner with ADK expertise can design and deploy a pipeline tailored to your workflows. 

How much does it cost to build an AI agent pipeline for a small business? 

Costs vary depending on complexity, the number of agents, and the integrations required. However, one of the main advantages of multi-agent architecture is that specialist agents are significantly cheaper to run than frontier AI models. A summarisation pipeline processing hundreds of interactions daily can cost pennies per task rather than pounds. Cardiff App Developers can provide a scoped estimate based on your specific requirements. 

Do I need an in-house development team to use Google ADK? 

No. Google ADK is a developer framework, but you do not need an internal team to benefit from it. Working with an experienced development partner, such as Cardiff App Developers, means you can have a production-ready agent pipeline designed, built, and deployed without needing to hire or train in-house engineers. 

How long does it take to implement a multi-agent system? 

A focused, single-pipeline implementation, such as an enquiry handling and routing system, can typically be scoped, built, and deployed within a matter of weeks depending on the complexity of your existing systems and data. More complex architectures with multiple integrated workflows take longer. Cardiff App Developers works iteratively, meaning you can start with one agent and expand from there. 

Can Google ADK integrate with tools my business already uses? 

Yes. ADK’s integration catalogue covers a wide range of business tools including CRM platforms, project management systems, databases, email and communications tools, and payment providers. If your business uses Asana, Jira, Notion, Stripe, or similar platforms, ADK agents can connect to and act on data within those systems. 

Is Google ADK open source? 

Yes. Google ADK is open source, which means developers can inspect, modify, and extend agent functionality. This gives organisations far greater flexibility than closed AI solutions and avoids vendor lock-in. 

Related Reading 

1. 3 Ways AI Can Save Your Business Thousands of Hours 

2. Ten Tech Trends Every SME Should Know About in 2026 

3. How to Choose the Right App Development Partner for Your Business 

4. 10 Questions Every Business Owner Asks Before Building a Digital Product 

5. Vibe Coding in App Development: Creative Shortcut or Risky Mistake? 

6. Cardiff App Developers Is Building for a Greener Future