Gartner has highlighted four emerging technologies that are shaping autonomous business. These are machine customers, artificial intelligence (AI) agents, decision intelligence and programmable money.
These are examined in the analyst giant’s new 2025 Hype Cycle for Emerging Technologies which provides a graphic representation of the maturity/adoption of technologies and applications and how they are potentially relevant to solving real business problems and exploiting new opportunities.
Gartner Hype Cycle methodology gives a view of how technology will evolve over time, providing a sound source of insight to manage its deployment within the context of specific business goals.
AI and automation are transforming modern businesses
“After years of digital transformation, organizations now face new disruption as AI and automation reshape competition, customers, products, operations and leadership,” said Marty Resnick, VP analyst at Gartner. “In this new autonomous business era, CIOs must assess how emerging technologies can create competitive differentiation, unlock greater efficiencies and capture new growth opportunities.”
4 technologies shaping autonomous business
The four emerging technologies shaping autonomous business are:
1. Machine customers
Machine customers are nonhuman entities that buy goods or services on behalf of individuals or organizations. According to Gartner, there are currently around three billion internet-connected B2B machines capable of acting as customers, a number expected to reach eight billion by 2030. Examples include virtual assistants, smart home devices, connected vehicles and IoT-enabled industrial equipment.
“Machine customers will play an important role in industries like manufacturing, retail and consumer goods, unlocking new revenue and efficiency opportunities,” said Resnick. “To capitalize, organizations must reimagine their business models or risk being left behind.”
2. AI agents
AI agents are systems capable of perceiving their environment, making decisions, taking action and pursuing goals, either in digital spaces or the physical world. Organizations are increasingly using technologies like large language models (LLMs) to build and deploy these agents to manage complex tasks. As a result, AI agents have the potential to transform industries such as customer service, manufacturing, data analysis, content creation and logistics by automating a wide range of work.
However, trust in AI agents is still developing. Concerns persist about their ability to reliably perform tasks and make accurate decisions, especially when operating without human supervision. These agents can act quickly (sometimes before humans are even aware) which raises risks.
Gartner advises organizations to include AI agents in their strategic planning by understanding their capabilities, limitations and practical applications, particularly as these agents become more autonomous and accessible.
3. Decision intelligence
Decision intelligence is a practical discipline focused on enhancing decision-making by analyzing and engineering how decisions are made and how their outcomes are assessed, managed and refined through feedback. By digitizing and modeling decisions as valuable assets, it helps close the gap between insights and actions, driving continuous improvements in decision quality, execution and results.
“Agentic AI and generative AI hype, regulatory pressures on decision automation and recent global uncertainty have revealed weaknesses in traditional business processes and decision making,” said Christian Stephan, senior director analyst at Gartner. “In response, organizations now demand decision processes that deliver speed and quality, but are also consistent, compliant, cost-effective and capable of handling complexity and change.”
4. Programmable money
Programmable money refers to digital currency that can be controlled by software, enabling it to operate based on predefined algorithmic rules. Often powered by blockchain, tokenization and smart contracts, it facilitates more dynamic and automated value exchanges, expanding participation across economic actors. As machine customers emerge as a new category of consumers, organizations will need to adopt programmable money to effectively interact with them, as well as with business partners and employees.
“Programmable money is transformative for financial services providers, enabling new forms of currency and digital asset markets,” said Stephan. “It drives innovation in value creation, financing and asset exchange, including machine-to-machine trading, reshaping supply and financial value chains.”