Managing the Machine, Managing the Self: Emotional Intelligence and the Future of AI-Assisted Decision-Making
The following article reflects on Deloitte's 2026 Global Human Capital Trends, "AI and the future of human decision-making", through the lens of one of the Psychomanagement team's active streams on emotional intelligence, trust in AI, and decision-making.
The tipping point Deloitte identifies
Deloitte's 2026 Global Human Capital Trends report dedicates a full chapter, called "AI and the future of human decision-making"(pp. 23–28), to a shift already underway inside organisations. According to the report, 60% of executives now regularly use AI to support their decisions, and Gartner projects that by 2027 half of all business decisions will be augmented or automated by AI agents. Boards are beginning to use AI to inform their choices as well.
Yet Deloitte is clear about the risk: as organisations expand AI-enabled decision-making, many find that AI is amplifying existing deficiencies instead of solving them. More than half of the organisations studied, operate at low decision-making maturity, but few teach decision skills, and only a small minority consider themselves to be leading the way. The report frames this as a moment of choice, one where hesitation carries lasting consequences.
Where the human factor becomes decisive
A recurring theme running through Deloitte's analysis is that technology alone does not determine decision quality; the human relationship to that technology does. Three findings from the chapter make the point.
The erosion of critical judgment: As workers increasingly rely on AI, 42% of executives are already concerned that employees are becoming overly dependent on it for essential cognitive tasks. Deloitte warns of deskilling and of workslop*, passable but shallow outputs that mask weak reasoning.
Trust as the value driver: Deloitte's Trustworthy AI research finds that workers who trust the AI agents they work with, are ten times more likely to see those agents as critical to creating value. People extend trust to technology when it demonstrates reliability, capability, transparency, and humanity.
Human agency and the "why": The chapter concludes that technology can accelerate analysis and clarify uncertainty, but it cannot replace the human purpose, values, and judgment behind choices. The goal is to keep humans "firmly in charge of the why."
Each of these findings points beyond models and governance frameworks toward something more personal: the emotional and interpretive capacity of the people making decisions. This is precisely the territory of one of the Psychomanagement team's current research streams examines; the way a decision-maker's emotional intelligence shapes trust in AI, acceptance of its outputs, and the effectiveness of the decision-making process.
Emotional intelligence as the connective thread
There is a further dimension the report highlights that is easy to overlook. Deloitte observes that AI itself is becoming steadily more empathetic, and that the intentional design of emotionally aware human-AI interaction is now treated as important to organisational success. This cuts both ways. As AI grows more emotionally fluent, the ability of the human user to interpret it, to distinguish an authentic, reliable response from a persuasive or manipulative one, becomes more, not less, important.
Emotional intelligence is the connective thread across the entire chain: it underpins the trust a user is willing to extend, the judgment that guards against over-reliance, the acceptance of AI outputs, and ultimately the agency to remain in charge of the decision. Where AI supplies speed and scale, emotional intelligence supplies discernment. The two are not in competition; the second is what makes the first safe to use.
Training managers to manage AI
Deloitte is explicit that this cannot be left to chance. Among its recommendations, the report calls directly for organisations to train managers to manage AI, noting that management skills now include managing machines as well as people; scoping agent autonomy, judging model outputs, and knowing when to override. These, the report observes, are likely new skills for most managers, and the challenge will only intensify as organisations flatten and spans of control widen. Deloitte adds a pointed observation: many organisations teach AI how to decide while assuming humans already know how to decide.
This is where the two literatures meet most productively. Managing AI well is not a purely technical competence; it is a relational and emotional one. A manager must read situations, calibrate trust, absorb ambiguity, and sustain the confidence of a team living through constant change, all while deciding when to defer to a machine and when to intervene. Our research team approaches this fusion through Psychomanagement, the integration of Emotional Intelligence and Leadership.
Under this lens, the manager who is asked to "supervise" AI is, first, a manager who must supervise their own emotional responses, model intact judgment for others, and lead people through the discomfort of technological transition. Training that develops emotional intelligence alongside leadership is not a soft add-on to AI adoption but core preparation for it.
Takeaway
Deloitte's 2026 chapter makes a compelling case that the future of decision-making will be defined not by how capable AI becomes, but by how thoughtfully humans engage with it. If organisations want to realise the "human advantage" the report champions, investment must reach the individual decision-maker and specifically the manager now tasked with governing both people and machines. Emotional intelligence, embedded in leadership through a Psychomanagement approach, is what turns AI from a source of risk into a genuine multiplier of human judgment.
*Workslop is a new corporate slang term used to describe low-quality, AI-generated content in the workplace that looks polished at first glance but lacks substance, accuracy, or real value.
[Source: Delloite | Decision-Making with AI]
