AI isn’t just the shiny new tool in your tech stack; it’s the future of competitive edge—if you know how to use it. Mikalef and Gupta’s study “Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance” dissects what it takes to turn AI from an underwhelming gadget into a game-changing organizational capability. Spoiler alert: AI itself isn’t enough. Instead, to achieve success with AI and creativity, businesses need to build “AI capability” by combining technology, data, human skills, and intangible resources like risk-taking and adaptability. The study’s resource-based theory (RBT) framework provides a clear roadmap for achieving this.
The authors argue that AI capability is the ability to select, orchestrate, and leverage AI-specific resources effectively. To validate their ideas, they surveyed 143 senior technology managers, unpacking the relationship between AI capability, organizational creativity, and firm performance. The verdict? Companies that develop strong AI capabilities enjoy greater innovation and improved performance metrics. However, achieving this isn’t as simple as buying better hardware or hiring a few data scientists.
AI capability relies on three pillars:
- Tangible resources like data and tech infrastructure. High-quality, well-organized data is the lifeblood of AI, while robust hardware and cloud solutions make AI scalable and efficient.
- Human resources including technical skills (e.g., data scientists who can handle machine learning) and business acumen (e.g., managers who know how to align AI with strategy).
- Intangible resources like inter-departmental coordination, organizational change capacity, and a willingness to take risks. These factors often separate leaders from laggards.
The study also highlights common hurdles—from resistance to change to data management issues—and emphasizes the importance of complementary investments in infrastructure, training, and culture. In essence, AI capability isn’t just about having the tools; it’s about knowing how to wield them strategically to foster a synergy between AI and creativity.
What Business Leaders Need to Know about AI and Creativity
Mikalef and Gupta’s research reveals several key insights that reshape how we think about AI’s role in business.
- AI capability integrates technology, human skills, and organizational processes to create value. It’s not just about having the right tools but about weaving them together in a way that supports innovation and decision-making. Organizations that master this integration can unlock transformative business outcomes.
- Firms with high AI capability outperform competitors in innovation and efficiency. These organizations leverage AI to streamline operations, develop groundbreaking products, and deliver customer experiences that set them apart. The edge they gain often translates into sustained market leadership.
- Intangible resources, like adaptability and inter-departmental coordination, are critical to unlocking AI’s potential. A culture of collaboration ensures that technical and business teams work in harmony, enabling faster adoption and more meaningful AI applications. Adaptability allows firms to pivot and innovate in a rapidly changing landscape.
- Resistance to change and poor data quality are significant barriers to AI adoption. Change management is as critical as the technology itself; without it, even the best AI initiatives falter. Similarly, without clean, well-structured data, AI models struggle to produce reliable insights, turning potential assets into liabilities.
- Effective AI deployment requires alignment across technical and business units. Collaboration ensures that AI solutions address real business needs rather than becoming siloed experiments. This alignment is the difference between AI as a buzzword and AI as a value driver for AI and creativity.
Real Quotes and Topics
These quotes from the study capture the essence of AI capability and its implications:”
- Definition of AI Capability: “An AI capability is the ability of a firm to select, orchestrate, and leverage its AI-specific resources.”
- Data as the Foundation: “High-quality data is considered critical, as it is used to train AI algorithms and derive meaningful insights.”
- Importance of Culture: “Inter-departmental coordination and a culture of collaboration are essential for deriving value from AI investments.”
- Role of Leadership: “Managers need to understand the potential applications of AI and lead change initiatives effectively.”
- Risk Proclivity: “Organizations with a strong proclivity for high-risk projects are more likely to gain a competitive edge through AI.”
Key Takeways for Using AI in Creative Processes
Based on the study’s findings, here are actionable steps business leaders can take to unlock the full potential of AI and creativity:
- Invest Beyond Tools: Don’t just buy the shiny AI toys. Invest in the foundation – infrastructure, training, and leadership – to actually make them work.
- Break Silos: Collaboration between technical and business teams isn’t just a nice-to-have; it’s essential. AI initiatives thrive when these groups share goals, communicate openly, and integrate their expertise into cohesive strategies.
- Prioritize Quality Data: Garbage in, garbage out. High-quality, well-organized data isn’t just helpful—it’s mission-critical. Strong data governance ensures AI models have the right inputs to produce actionable insights.
- Foster Adaptability: Resistance to change is a dealbreaker. Organizations must cultivate a culture that sees new technology as an opportunity rather than a threat, making adaptability a core competency.
- Take Calculated Risks: Risk-takers win big with AI, but reckless moves can backfire. Successful leaders balance bold strategies with careful planning, turning risks into competitive advantages.
- Think Long-Term: AI payoffs aren’t instantaneous. Focus on scalable pilots, measure incremental wins, and align these with broader organizational goals to sustain momentum over time.
- Align AI with Strategy: AI projects should be more than shiny experiments; they need to drive tangible business value. When AI initiatives align with strategic goals, they become powerful tools for growth and differentiation.
5. Discussion/Reflection Questions
To further explore the implications of this research within your organization, consider these discussion points:
- What steps can your organization take to integrate technical and business teams for seamless AI adoption?
- How does your company’s leadership support or hinder the implementation of AI initiatives?
- What strategies can ensure your data infrastructure is ready for advanced AI applications?
- How can your organization overcome resistance to change and build a more adaptable culture?
- Are your AI initiatives aligned with broader organizational goals, or are they isolated experiments?