AI Perspectives #7: AI as a Strategy

Rethinking Business in the Age of Intelligent Systems

Feb 11, 2025

Introduction

AI Beyond a Productivity Tool

The widespread integration of artificial intelligence (AI) into business operations has been predominantly approached from a functional perspective—enhancing efficiency, automating repetitive tasks, and optimizing decision-making processes. While these applications are valuable, they represent only a fraction of AI’s potential impact. Many organizations, particularly small and medium-sized enterprises (SMEs), are incorporating AI incrementally rather than recognizing it as a fundamental driver of competitive advantage.

A strategic approach to AI requires a shift in mindset. AI is not merely a tool that supports existing business processes; it is a transformative force that reshapes industries, alters economic structures, and influences long-term sustainability. Organizations that position AI as a strategic priority, rather than a technical enhancement, are better equipped to navigate emerging market conditions, create new value propositions, and maintain resilience in an increasingly AI-driven economy.

What’s Happening?

AI Adoption in SMEs

Recent reports indicate that AI adoption among Small and Medium-sized Enterprises (SMEs) is steadily growing, with many businesses recognizing its potential to drive growth and improve operations. A survey by BGF found that 89% of SME leaders view AI as an opportunity for growth1, while an OECD report2 revealed that 35% of mostly digitalized businesses reported using AI technologies. SMEs are primarily adopting AI-powered tools rather than developing AI in-house, with popular applications including Customer Relationship Management (CRM) systems, chatbots, virtual assistants, and marketing automation platforms.

Despite the positive trend, SMEs face challenges in AI adoption, including skills gaps, resource limitations, and awareness issues. However, the outlook remains optimistic, with 78% of SMEs using AI saying it will be a game-changer for their company3. One-third of companies have already dedicated budgets to AI, and nearly 40% plan to do so within the next year4. The development of user-friendly AI tools with no-code interfaces is making AI more accessible to SMEs, further driving adoption rates. As AI continues to prove its value in improving efficiency and competitiveness, it's likely that more SMEs will integrate AI technologies into their operations in the coming years.

Business Impact of AI on SMEs

Real-world cases demonstrate that AI has significantly improved productivity, sales, and efficiency for SMEs. A small online fashion boutique increased sales by 30% within three months by implementing an AI-powered recommendation engine. A mid-sized coffee shop chain reduced labor costs by 15% and decreased customer wait times by 20% using AI-powered workforce management. An e-commerce store selling handmade crafts cut customer service costs by 40% with AI chatbots. A family-owned bakery doubled social media engagement and increased online orders by 25% using AI-powered social media management. An HVAC company increased lead generation by 50% and grew revenue by 20% within six months using AI-powered sales tools. These examples showcase the tangible benefits of AI adoption across various industries and business functions.

The economic impact of AI adoption on SMEs in the next 5-10 years is expected to be substantial. According to a report by Accenture, companies that adopt AI in their workflows could see a 38% increase in productivity by 20355. McKinsey predicts that 70% of companies will be using AI significantly in their businesses within the next five years[5]. The projected annual investment in AI is expected to reach $340 billion during 2025, indicating a growing recognition of AI's importance in maintaining competitiveness[5]. While specific measurable differences between AI-adopting SMEs and non-adopters are not provided in the search results, the numerous success stories and projected growth figures suggest that SMEs leveraging AI are likely to outperform their non-AI-using counterparts in terms of efficiency, customer engagement, and revenue growth.

Defining AI as a Strategy

The distinction between AI as a tool and AI as a strategy lies in the scope and depth of its integration within an organization. AI as a tool is primarily focused on operational improvements—reducing costs, increasing automation, and optimizing workflows. It is reactive, addressing specific challenges through targeted applications. In contrast, AI as a strategy is proactive, encompassing a broader vision in which AI fundamentally informs business models, competitive positioning, and long-term decision-making.

Several characteristics define AI as a strategic approach:

AI Shapes Core Business Models – Rather than being an auxiliary technology, AI becomes embedded in how value is created, delivered, and captured. In some cases, AI may drive entirely new business models that were previously unfeasible.
AI Redefines Competitive Advantage – Traditional sources of competitive differentiation, such as economies of scale, may become secondary to AI-enabled agility, predictive analytics, and automated decision-making.
AI Becomes a Governance Priority—Integrating AI at a strategic level requires governance frameworks that address ethical considerations, regulatory compliance, and long-term sustainability. Decision-making related to AI must extend beyond technical departments to executive leadership and board-level discussions.

Strategic vs. Tactical AI Implementation

The distinction between tactical AI adoption and a strategic AI-driven approach can be observed across multiple industries.

Companies that have successfully integrated AI at a strategic level are characterized by their ability to redefine industry standards. For example, leading e-commerce platforms do not simply use AI to enhance marketing campaigns or optimize logistics; they build AI-driven ecosystems that influence pricing strategies, consumer behavior, and supply chain operations in ways that are structurally embedded in their business models.

The Risks of a Fragmented AI Approach

Organizations that treat AI as an operational tool rather than a strategic asset face several risks:

Inability to Compete with AI-Driven Market Leaders—Companies that integrate AI into core strategic planning are often able to scale more rapidly, respond more effectively to market shifts, and introduce innovations at a pace that outperforms competitors relying on traditional business models.
Limited Long-Term Adaptability – AI-driven industries evolve rapidly, and organizations that fail to incorporate AI into strategic decision-making may struggle to adapt to changing market dynamics.
Missed Opportunities for Innovation – AI is not solely a means of improving existing operations; it enables entirely new forms of value creation. Businesses that focus solely on automation may overlook opportunities for industry-wide transformation.

Pathways to AI-Driven Strategic Thinking

Transitioning from an AI-as-a-tool mindset to an AI-as-a-strategy framework requires a structured approach:

Executive-Level AI Literacy – Leadership teams must develop a foundational understanding of AI’s strategic implications. This includes not only technical awareness but also an appreciation of AI’s potential impact on business models, regulatory environments, and economic structures.
Cross-Functional AI Integration – AI should not be confined to IT departments. It must be integrated across finance, operations, marketing, and strategic planning functions to ensure alignment with long-term business objectives.
Investment in AI Governance and Ethics – A strategic approach to AI necessitates governance frameworks that address biases, data privacy, and compliance with evolving regulatory landscapes.
Exploration of AI-Driven Business Model Innovation – Organizations should assess how AI can facilitate the development of new revenue streams, partnerships, and customer engagement models.

Conclusion

AI as the Foundation for Future Business Strategy

As AI continues to evolve, its role in shaping competitive dynamics will extend beyond automation and efficiency gains. Organizations that recognize AI as a core strategic pillar will be better positioned to navigate uncertainty, drive innovation, and achieve sustainable growth. The question is not whether AI will play a role in business transformation, but whether organizations will proactively integrate AI into their strategic vision or remain constrained by a limited, tool-based approach.

By shifting AI from a tactical implementation to a long-term strategic asset, organizations can leverage its full potential—not only to optimize operations but to redefine industries and economic landscapes.

Taking Action: Integrating AI as a Strategy

The shift to an AI-driven strategy requires a proactive and multifaceted approach. Here's how businesses can begin this journey:

Invest in AI Literacy
1. Leadership Education: Provide training and resources for executives and decision-makers to understand AI's strategic implications beyond its technical aspects.
2. Cross-Functional Awareness: Educate teams across different departments (finance, marketing, operations) about AI's potential to impact their roles and the broader business strategy.
Foster a Culture of AI Innovation
1. Encourage Experimentation: Create a safe space for teams to explore and experiment with AI tools and applications.
2. Support Collaboration: Facilitate cross-functional collaboration to identify AI opportunities and develop innovative solutions.
3. Celebrate Successes: Recognize and reward teams that successfully implement AI initiatives.
Develop an AI Governance Framework
1. Establish Ethical Guidelines: Define clear ethical principles for AI development and deployment to ensure responsible use.
2. Address Data Privacy: Implement robust data governance policies to protect customer privacy and comply with regulations.
3. Monitor and Adapt: Continuously monitor the impact of AI initiatives and adapt governance frameworks as needed.
Explore AI-Driven Business Model Innovation
1. Identify New Opportunities: Assess how AI can be used to create new products, services, or revenue streams.
2. Reimagine Customer Experiences: Explore how AI can personalize and enhance customer interactions.
3. Optimize Operations: Utilize AI to streamline processes, improve efficiency, and reduce costs.
Seek External Support
1. Consult with Experts: Engage with AI experts to gain insights and guidance on AI strategy and implementation.
2. Partner with AI Providers: Collaborate with AI technology providers to access cutting-edge tools and solutions.
3. Join Industry Networks: Connect with other businesses and organizations to share knowledge and best practices in AI adoption.

https://ceoworld.biz/2024/11/12/ai-adoption-gains-traction-among-smes-bgf-survey-shows/

https://www.oecd.org/content/dam/oecd/en/publications/reports/2024/09/sme-digitalisation-to-manage-shocks-and-transitions_735fc44d/eb4ec9ac-en.pdf

https://www.salesforce.com/news/stories/smbs-ai-trends-2025/?bc=OTH