As companies move beyond experimenting with artificial intelligence, they’re confronting a new set of practical questions. Who has the expertise to turn promising technology into working solutions? How much will it cost to deploy and maintain those systems? And how can businesses ensure their investments deliver meaningful returns? This collection of McKinsey Explainers examines the people, processes, and costs behind successful AI adoption.
One increasingly important role is the forward-deployed engineer, a specialist who works within companies to develop tailored solutions. Martin Harrysson explains that the role requires more than technical know-how: Engineers must understand how decisions are made, identify opportunities to improve processes, and work with employees to ensure new tools deliver results. Nick Robson adds that getting the most from AI often requires companies to rethink their workflows and how employees interact with technology.
These choices can have significant financial implications. According to research cited by Kaavini Takkar, AI spending nearly quadruples on average when projects move from pilot to production. And as Wasim Lala points out, a poorly designed agent can consume up to 30 times as many tokens as an efficient one. In the Explainer “What does AI really cost?,” Takkar, Lala, and Lari Hämäläinen examine why AI costs can be difficult to predict and how companies can better assess whether their investments are paying off.
For more on how emerging technologies are reshaping industries, software development, and the way businesses operate, explore the Explainers below.
What is a forward-deployed engineer?
AI in five industries: What’s now, and what’s next
AI-powered software development: How technology is rewriting the rules
Where AI is creating real value in real estate
Agentic AI explained: When machines don’t just chat, but act