Today, users and organizations are experimenting with and deploying solutions that, just a decade ago, would have been prohibitively time-consuming, complex, and expensive. One of the most transformative developments driving this shift is the rapid rise of AI and generative AI (GenAI). Noteworthy shift is occurring in the realm of automation. The gap between the tools and concepts used by large enterprises and those available to small and medium-sized businesses (SMBs) is narrowing. Interestingly, even large enterprises often begin their AI initiatives with small pilot projects - approaches that closely resemble those taken by SMBs.
Of course, there is no rose without a thorn. To the old adage about automation - “garbage in, garbage out,” which highlights the importance of data quality and relevance - we must now add concerns about the “black box” nature of many AI systems. For most users, AI remains opaque, making expertise more critical than ever for successful deployment.
Author
Alexander Zagnetko
Manager, Process Organization and Improvement
Agentic AI among the top technology trends for this year and beyond
Agentic AI is currently one of the most talked-about topics in the tech world. Conferences, thought leadership pieces, vendor press releases, and industry gurus are all touting its transformative potential - promising significant benefits for those who adopt early. Leading analyst firms have named agentic AI among the top technology trends for this year and beyond, forecasting that within three years, nearly half of the solutions used by organizations will incorporate some form of agentic AI capabilities.
Yet despite the buzz, many organizations still struggle to define what agentic AI actually is. As a result, their understanding of its potential advantages - and its risks - is often vague or incomplete. This is where the KPMG TACO framework becomes especially valuable. Designed to support both large enterprises and SMBs, the framework helps organizations make sense of agentic AI, maximize the value of new solutions, and proactively manage the associated risks.
KPMG TACO Framework: A guide for SMBs
In the rapidly evolving world of AI, businesses of all sizes are exploring how to integrate intelligent systems into their operations. The KPMG TACO Framework offers a structured approach to understanding and deploying AI agents in a way that is scalable, responsible, and aligned with business goals. While originally designed with large enterprises in mind, the framework holds significant value for SMBs looking to harness AI effectively.
The TACO Framework categorizes AI agents into four types based on their level of autonomy and complexity. This classification helps organizations match the right type of agent to the right use case, ensuring that AI is applied where it delivers the most value.
T – Taskers: Perform simple, well-defined tasks. These agents often require human oversight and are ideal for repetitive, rule-based activities.
A – Automators: Handle more complex, repeatable processes with minimal human intervention. They are useful for streamlining workflows and improving efficiency.
C – Collaborators: Work alongside humans, adapting to context and providing intelligent support. These agents can assist in decision-making and customer interactions.
O – Orchestrators: Coordinate multiple agents and systems to achieve broader business goals autonomously. They represent the most advanced form of agentic AI.
Why is it useful for small and medium businesses?
While SMBs may not have the same resources as large enterprises, they often have the agility to adopt new technologies quickly. There are several ways the TACO framework can support them. It offers a clear and easy-to-understand taxonomy of AI agents, making AI strategy planning more structured and focused. It enables a smooth transition from basic automation to more advanced solutions, supporting a gradual and scalable expansion of AI capabilities. Finally, the framework helps bridge the gap between IT, operations, and business units by providing a shared language and structure for implementing AI initiatives.
Key benefits of the TACO framework
- Easy start with clear impact
SMBs can begin with Taskers or Automators to handle repetitive tasks like invoice processing, customer support, or data entry—freeing up staff for higher-value work. - Improve customer experience
Collaborators can enhance customer service by providing intelligent chatbots or virtual assistants that learn and adapt over time. - Optimize operations
Automators and Orchestrators can streamline supply chains, manage inventory, or coordinate marketing campaigns, improving efficiency and reducing costs. - Build trust with stakeholders
By embedding governance into AI systems from the start, SMBs can demonstrate responsibility and transparency to customers, partners, and regulators. - Future-proofing
As AI capabilities evolve, the TACO Framework provides a roadmap for scaling up without losing control or clarity.
Getting started
If you're considering adopting the TACO framework, the first step is to identify areas where automation can quickly deliver added value — for example, by streamlining repetitive processes. Next, it’s important to assess the readiness of your existing systems and data infrastructure. Based on the TACO classification, you can then choose the type of agent that best fits the specific task at hand. Every AI solution should also include governance mechanisms to ensure ethical, legal, and operational responsibility. Finally, it's essential to approach AI development as a gradual journey — learning from initial projects and steadily expanding both their scope and impact.
The KPMG TACO Framework is more than just a classification system - it’s a strategic tool for building intelligent, responsible, and scalable AI systems. For SMBs, it offers a practical path to innovation, helping them compete more effectively in a digital-first world.
At KPMG, we’ve developed a range of frameworks and solutions to support organizations in their AI journeys. Our portfolio includes numerous successful use cases, from SMB-focused projects to quick wins achieved without significant investment.
One such initiative is KPMG AI Jumpstart, a program designed to help organizations - especially small to medium-sized businesses - begin their AI journey with low-risk, high-impact pilots that can quickly demonstrate value. It helps businesses explore AI opportunities, experiment with real use cases, and execute pilots that are scalable and aligned with business goals. It’s particularly suited for organizations looking for quick wins without heavy upfront investment.
Practical applications
- Internal audit automation
A company automated its entire internal audit lifecycle - from scoping to reporting - using AI. This eliminated repetitive tasks and enabled auditors to focus on risk insights, not spreadsheets - Route planning
A mid-sized logistics company used AI Jumpstart to optimize route planning and reduce fuel costs by 12% within 3 months - Customer service chatbots
SMEs in retail and services deployed AI chatbots to handle FAQs and basic support, reducing call center load by up to 40%. - Invoice processing automation
A mid-sized logistics firm used AI to extract and validate data from invoices, cutting processing time by 60% and reducing errors. - Sales forecasting
A regional distributor implemented AI models to predict sales trends, improving inventory planning and reducing stockouts.
If you decide to embark on this journey, KPMG is ready to be your partner — offering expertise, tools, and a human-centered approach. We firmly believe that artificial intelligence isn’t just for the big players; smaller companies can also harness its power to achieve their goals.
Contact us
Should you wish more information on how we can help your business or to arrange a meeting for personal presentation of our services, please contact us.
