The latest developments in generative AI, including ChatGPT, have suddenly propelled interest in AI —  not just as a technology or business tool but as a general product technology. AI is making an impact on society comparable to the advent of the internet, printing press or even electricity. It’s on the verge of reshaping society as a whole.

Among Gartner strategic planning assumptions for AI are that:

• By 2026, organizations that operationalize AI transparency, trust and security will see their AI models achieve a 50% improvement in terms of adoption, business goals and user acceptance.

• By 2026, enterprises that have adopted AI engineering practices to build and manage adaptive AI systems will outperform their peers in the number and time it takes to operationalize AI models by at least 25%.

• By 2027, at least two vendors that provide AI risk management functionality will be acquired by enterprise risk management vendors providing broader functionality.

• By 2027, at least one global company will see its AI deployment banned by a regulator for noncompliance with data protection or AI governance legislation.

The key emerging techniques, in descending order of maturity are:

• Natural language processing (NLP). NLP provides intuitive forms of communication between humans and systems. NLP includes computational linguistic techniques (symbolic and subsymbolic) aimed at recognizing, parsing, interpreting, automatically tagging, translating and generating (or summarizing) natural languages. 

• Knowledge representation. Capabilities such as knowledge graphs or semantic networks aim to facilitate and accelerate access to and analysis of data networks and graphs. Through their representations of knowledge, these mechanisms tend to be more intuitive for specific types of problems. Adoption of knowledge graph techniques has accelerated quickly over the last three years.

• Agent-based computing. This is the least mature of the established AI techniques, but it is quickly gaining in popularity. Software agents are persistent, autonomous, goal-oriented programs that act on behalf of users or other programs. Chatbots, for example, are increasingly popular agents.

Two main classes of agent applications are commonly used with existing solutions today:

• Task automation agents can be generic (e.g., meeting scheduling assistants in email systems) or more specific (e.g., contract validation softbots for sales automation applications).

• Autonomous object programs can serve functions such as automatic temperature-setting (e.g., found in car diagnostic systems or home thermostats).