Many organizations are eroding the fundamentals of their business: productivity, competitiveness, and efficiency. According to cloud data and AI consultancy Datatonic, this is due to poor implementation of human-AI collaboration. The company says that in the next phase of enterprise AI, success will come from carefully managed and designed AI working alongside humans in “human-in-the-loop” (HiTL) systems.
The company’s research shows that companies that fail to integrate AI into human workflows are less productive and fall behind the competition. Datatonic says its hybrid human-AI approach speeds up decision-making and improves overall operations. Scott Ivers, CEO of Datatonic, said, “AI is about redesigning the way work is done. The biggest risk we see in the market is productivity leakage when AI exists in isolation from the people who actually run the business.”
After years of investing in AI, the pressure on companies to make a profit is increasing. However, some research indicates that some initiatives remain in the experimental phase due to limited trust among users. As a result, organizations are unable to leverage AI-powered insights to positively impact decisions and workflows, and efficiency gains never materialize.
According to Datatonic, HiTL models are critical to future success, offering a combination of the speed of AI and human judgment and accountability. This is evident in agent-assisted software development, where AI systems create code from loose prompts and translate them into code. In this case, a human team decides what needs to be developed, inspects all requirements, and reviews the plan before realizing it. Once this direction is clear, the AI agent builds modular components.
The trend of AI in the workplace is also starting to appear in the finance and operations fields. For example, in back-office and finance departments, AI-powered document processing is already reducing invoice processing costs by 70%, according to some sources, yet finance teams still approve the final results.
“This is a story of partnership,” says Andrew Harding, CTO of Datatonic. “Humans create evaluation systems, validate plans, set guardrails, and make decisions. AI executes at speed and scale. That combination delivers real enterprise value.”
According to Datatonic, many enterprises are unable to securely deploy fully autonomous agents due to a lack of security management and governance frameworks. Autonomy can only be extended if organizations implement approval checkpoints and benchmark performance standards. As AI models evolve, evaluation systems must also be implemented to ensure they always operate safely and as intended without violating compliance obligations.
“As trust builds, companies will be able to responsibly delegate more to AI,” Harding said. “But cutting out governance doesn’t increase speed; it creates risk.”
Datatonic predicts that workloads will accelerate significantly over the next two years as preparation and validation are handled by AI agents. You can also implement AI systems to test and override decisions before your team invests resources.
In the future, Scott Ivers said, “we will see specialized functions run by smaller, more nimble teams like finance, human resources, and marketing, each powered by AI. The companies that win will be the ones that teach people to work with AI, rather than leveraging it.”
(Image source: “Waterfall” by PMillera4 is licensed under CC BY-NC-ND 2.0.)
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