Read this in The Manila Times digital edition.
ARTIFICIAL intelligence has evolved from a helpful add-on into an active partner in the modern workplace. Recent research from Harvard Business School (HBS), spanning leadership, workforce attitudes, teamwork experiments, decision-making and talent strategy, paints a consistent picture: AI is reshaping creativity, productivity and how people make decisions. But its promise depends on how organizations design work, govern systems and invest in people.
Early applications of generative AI focused on drafting emails and summarizing reports. Today, however, agentic AI — autonomous systems that can plan, reason and execute workflows — is taking on a larger role. HBS Naylor Fitzhugh Professor of Business Administration Tsedal Neeley and Expedia Group executive Ritcha Ranjan argue that these systems can function as a digital support team for leaders.
As Neeley puts it, “I can’t see a future without every individual using AI to dramatically improve their work, their relationships and their collaborations.” When deployed thoughtfully, agentic AI can free people to focus on higher-order strategy, innovation and creative work.
AI’s productivity benefits extend beyond doing tasks faster. They are changing the nature of work itself. In a field experiment at Procter & Gamble, researchers found that generative AI, used as a “cybernetic teammate,” delivered measurable gains in quality. Teams using AI were three times more likely to generate ideas that ranked in the top decile of quality, while individuals assisted by AI matched the performance of two-person teams working without it. As the study notes, “If you want to be in that top 10 percent of performers, a full human team plus AI seems like the recipe for success.”
The research also suggests that AI broadens participation. Employees with less experience achieved results comparable to those of more seasoned colleagues, indicating that AI can democratize expertise and unlock creativity across organizations.
The findings underscore the importance of mindset and practice. Leaders should view AI as a teammate rather than merely a tool, provide targeted training on how to work effectively with AI, and adopt different AI strategies depending on organizational goals. Ranjan highlights its operational value: “It could really help leaders stay ahead of emerging developments and get the insights to act.”
Practical steps include automating repetitive, low-value tasks to build trust in AI systems, expanding access so employees can experiment and learn, and training teams together to accelerate adoption. Equally important are safeguards such as human-in-the-loop oversight, ethical data use and transparent communication about how AI is being applied.
Public attitudes, ethical concerns
Workforce and customer acceptance remain critical factors. A large-scale survey found broad support for AI augmenting human work, with 94 percent of respondents supporting current-day AI applications. Acceptance increased when AI demonstrably outperformed people. At the same time, respondents identified clear moral boundaries. Certain professions, including clergy, childcare workers and funeral directors, were viewed as inappropriate for automation, while nearly 42 percent of occupations generated mixed views about AI replacement.
Assistant Professor James Riley frames the issue succinctly: “It’s a question of whether we can do even more at our jobs with these tools than we would have been able to in the past.”
For business leaders, the lesson is clear. Performance gains must be weighed against stakeholder expectations and reputational risks. Transparency matters, as does prioritizing automation in areas where it will not diminish customer value or erode trust.
Research on algorithmic decision-making reveals a similar nuance. People generally prefer human involvement in high-stakes decisions such as loan approvals or pretrial release assessments. However, they are more willing to accept algorithmic recommendations when evidence shows that those systems outperform human decision-makers in terms of accuracy and risk reduction.
Assistant Professor Elisabeth Paulson’s findings suggest that decision quality often carries more weight than abstract concerns about fairness. The implication for organizations is straightforward: rigorously validate algorithmic performance, communicate the results transparently and consider hybrid models in which algorithms inform decisions while humans retain final authority and accountability.
Winning with AI depends on people
Success with AI is as much about people as it is about technology. Boris Groysberg, Richard P. Chapman Professor of Business Administration, emphasizes the importance of “talent density.” Hiring top performers is important, but organizations must also integrate teams effectively, design strong processes and preserve the uniquely human capabilities that AI cannot replicate.
Groysberg cautions that simply assembling talented individuals does not automatically create a cohesive team. “There’s still an attitude of ‘Let me get the great people, and they’re going to evolve and merge into a team,’” he said.
He offers a memorable reminder of the human role in an AI-enabled workplace: “AI will give you the alphabet, but you still need to write a poem.”
Judgment, experience, leadership and influence remain distinct human strengths that technology alone cannot provide.
A pragmatic
and optimistic
path forward
AI’s influence on creativity, productivity and decision-making is neither automatic nor uniform. The evidence from HBS points to a practical playbook: begin with repetitive tasks, expand access and shared learning, keep humans involved in critical decisions, validate algorithmic performance and build talent systems that strengthen the human skills AI cannot replace.Organizations that follow this approach will not simply work faster. They will work smarter, more creatively and more effectively. The future is not about AI replacing people. It is about people working alongside increasingly capable AI partners to ask better questions, uncover deeper insights and make better decisions.