AI offers the potential to be a game-changer for businesses, promising to streamline operations, boost efficiency and drive profitability. While this potential is undeniable—especially with rapid advancements expected this year—its impact depends on the tools organizations eventually select and how they implement these capabilities. Many businesses invest in AI-driven solutions expecting instant transformation, only to find that the technology doesn’t integrate with their existing systems, fails to deliver measurable benefits or creates new inefficiencies.
The challenge for many organizations, especially small and midsize businesses, isn’t just adopting AI—it’s adopting the right AI. The best solutions go beyond hypothetical benefits and provide measurable, long-term value.
Business leaders are best served by adopting a strategic approach when investing in AI to effectively achieve their goals. Decision-makers can use the following five-step framework to evaluate AI solutions to ensure they align with business objectives, integrate seamlessly into operations, and drive real-world impact.
Step 1: Identify a Clear Business Problem AI Can Solve
AI adoption should start with a fundamental question: What specific challenge does this technology need to address? Too often, organizations implement AI without a clear strategy, choosing solutions based on hype rather than necessity. Without a well-defined problem to solve, AI risks becoming an expensive add-on rather than a valuable business tool.
In construction, for example, project delays are a constant challenge. AI-powered scheduling solutions can analyze historical data, weather conditions and supply chain logistics to optimize project timelines and reduce costly setbacks. In manufacturing, unplanned equipment downtime can lead to significant financial losses, making AI-driven predictive maintenance an invaluable tool to anticipate a need for proactive maintenance before a failure happens. Retailers facing changing consumer demand can leverage AI-powered forecasting to optimize inventory levels and avoid stock shortages or overstock issues.
By identifying the core operational challenges best suited to benefit from AI, businesses can ensure that the technology serves a meaningful purpose and delivers a direct return on investment.
Step 2: Ensure Executive Alignment on AI Strategy and Integration
AI adoption requires a broader transformation of business processes, strong leadership and strategic alignment. Poor integration with existing infrastructure remains among the biggest barriers to AI success, making it critical that business leaders drive transformation from the top down. While 90% of executives expect AI to boost revenue within three years, 70% of digital transformations fail, often due to a lack of leadership alignment. AI must be woven into business operations, not treated as a standalone tool. Leaders must champion AI initiatives, align teams on a clear vision and integrate AI with broader business objectives.
For instance, AI-powered invoice processing in distribution and professional services can automate and accelerate accounts payable workflows. However, if the tool doesn’t seamlessly sync with an organization’s financial systems, it can create more bottlenecks than efficiencies. Similarly, AI-driven demand forecasting in retail is only effective when it integrates with real-time sales data and inventory systems.
AI succeeds when leadership drives adoption as a part of a broader digital transformation strategy. With executive alignment on vision, value, and roadmap, AI becomes a competitive advantage woven seamlessly into day-to-day operations.
Step 3: Evaluate Security, Privacy and Compliance Risks
AI’s ability to process large amounts of data creates potential security and compliance risks. Since businesses handle sensitive information such as financial data, customer records and proprietary insights, AI systems must include the right safeguards to prevent unauthorized access, data breaches and regulatory violations.
Companies operating in regulated industries must ensure that AI solutions comply with data privacy laws such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). In addition to compliance, AI decision-making must be transparent. Black-box AI systems, where outcomes are generated without clear reasoning, pose risks in high-stakes environments, especially with regulatory oversight.
To limit these risks, business leaders should choose AI platforms prioritizing data governance and providing robust, built-in privacy controls. By embedding AI within a secure framework, organizations can leverage the extensive benefits of AI while following industry regulations and maintaining customer trust.
Step 4: Use AI to Enhance Human Decision-Making
One of the biggest misconceptions about AI is that it’s meant to replace human workers. While automation is crucial in improving efficiency, the most effective AI systems are designed to support and enhance human expertise rather than eliminate it. Studies show that AI can improve worker performance by nearly 40%. However, AI should not replace employee oversight, especially in industries where decision-making requires critical thinking and specialized expertise.
For AI to be effective, it must work alongside employees, allowing them to streamline tasks and access in-depth insights to make informed decisions. Businesses should consider investing in AI solutions that foster collaboration between technology and their teams.
Step 5: Establish Clear Metrics for Success
An AI investment is only valuable if it delivers measurable results. Yet, many businesses struggle to assess the true impact of their AI solutions. Without clear benchmarks, companies risk implementing AI tools that sound promising on paper but fail to translate into real business improvements.
To evaluate AI’s effectiveness, organizations should define success metrics before deployment. Key metrics could include factors such as cost savings, productivity gains or customer experience improvements. If AI is designed to automate workflows, businesses should measure reductions in manual processing time. If AI is being used to improve customer communication, organizations should track response times and customer satisfaction. By continuously monitoring AI’s performance, businesses can refine their approach and ensure that AI investments deliver the highest value for the company’s specific needs.
Turning AI Investments Into Competitive Advantages
AI offers the potential to transform the way we work, but businesses must take a strategic approach to evaluating and adopting AI tools in a way that works best for their organization and workforce.
Organizations that align AI with real business challenges, integrate it seamlessly with existing workflows, prioritize security and compliance and ensure it enhances human expertise will gain the most value from their investments.
By Miten Mehta, chief engineering officer, Acumatica