Four tips to identify AI solutions that solve real business problems

Artificial intelligence (AI) has the potential to become the most transformative technology of our time. With 89% of Harvard Business Review survey respondents acknowledging AI’s potential, businesses are under increasing pressure to integrate AI into their operations.

However, decision-makers face a significant challenge: How do they separate AI hype from AI that delivers tangible business value? Many AI solutions promise efficiency, automation and intelligence but fail to provide tangible operational benefits. Businesses of all sizes, particularly small and mid-sized organizations, must ensure that AI investments don’t just lead to cosmetic enhancements to existing features. Instead, the technology should deliver innovations that are genuinely integrated into workflows to enhance decision-making and deliver measurable results.

The following provides a helpful framework for business leaders to evaluate AI capabilities focusing on operational impact. Instead of getting lost in the hype, decision-makers can identify AI tools that work for them and drive meaningful results.

Tip 1: Align AI with Business Objectives

AI can deliver significant benefits across departments and business functions and is most valuable when it serves a clear, measurable business goal. While AI has broad applications, organizations should prioritize solutions that directly address specific business challenges rather than adopting AI just for the sake of “innovation.”

To understand what types of AI technology can drive the most business value, decision-makers should:

• Define business challenges. Start by identifying the organization’s biggest pain points. Some examples include operational inefficiencies, gaps in data analysis and a lack of automation.
• Identify where AI can enhance operations and decision-making. AI should enhance workflows, helping teams work smarter by reducing manual processes, minimizing errors and providing real-time insights for better decision-making.
• Focus on AI’s ability to reduce costs, increase productivity and improve customer experiences. Quantify AI’s potential by identifying specific areas where it can drive measurable impact. For productivity gains, prioritize AI solutions that personalize interactions, reduce response times and anticipate customer needs before they arise.

Once leaders determine business objectives, they should identify how to integrate AI technology into established processes.

Tip 2: Prioritize Data and Workflow Integration

One of the biggest pitfalls of AI adoption is investing in technology that doesn’t integrate smoothly into existing workflows. Thirty-eight percent of businesses say their biggest challenge in implementing AI is insufficient IT infrastructure. AI should complement Enterprise Resource Planning (ERP), Customer Relationship Management (CRM) and other operational systems, not create additional work or fragmented processes that lead to data siloes.

For AI to deliver accurate insights, it must be powered by comprehensive, real-time and accurate data across the organization. When AI pulls from disconnected data sources, it can generate misleading outputs that produce inaccurate results, thus hindering business growth. Business and tech leaders should confirm that the AI tool embeds easily into everyday workflows rather than requiring employees to use entirely new platforms.

A best practice is prioritizing cloud-based AI solutions that integrate natively with IT management software to ensure smooth data flow across departments. Unlike siloed on-premises systems that require manual data transfers, cloud-based AI tools can continuously sync information across ERP, CRM and other critical platforms, providing a single source of truth for decision-making.

Finally, AI-driven automation should reduce manual tasks and accelerate productivity without creating inefficiencies. For example, AI-powered demand forecasting can help supply chain managers accurately anticipate inventory needs by analyzing historical sales data, seasonal trends and market fluctuations. Instead of relying on manual calculations or gut instinct, businesses can optimize inventory, reduce waste and avoid running out of products.

Tip 3: Focus on Privacy, Security and Compliance

As AI adoption accelerates, concerns around data privacy, security and regulatory compliance grow. Businesses must ensure their AI investments follow strict security protocols to mitigate risks such as unauthorized data access, compliance violations and AI model bias. Without proper safeguards, AI can expose sensitive information or generate unreliable outcomes that could impact business operations.

To avoid these risks, leaders should ensure the following:

• AI models follow strict data governance policies and privacy regulations (e.g., GDPR, CCPA).
• AI-driven decision-making is auditable and transparent, ensuring explainability in high-stakes environments like finance and healthcare.
• Use cloud ERP platforms with built-in AI capabilities to provide more secure, centralized control over business data.
• The AI system protects private data through isolation from public LLM training.

Organizations can leverage AI’s power confidently by embedding AI within a secure framework. As they prioritize security, they will drive innovation without sacrificing trust and integrity.

Tip 4: Use AI to Enhance, Not Replace, Human Decision-Making

Studies show AI improves a worker’s performance by nearly 40% compared with workers who don’t use it, and the best AI solutions empower employees rather than replace them. AI should augment human expertise by surfacing predictive insights, automating repetitive tasks and minimizing errors, but final decision-making should remain with employees.

To maximize the technology’s value, AI must help employees make informed decisions rather than fully automating critical functions. Insights derived from AI-powered solutions should be clear and explainable, avoiding “black box” decision-making where employees can’t understand or validate AI-generated recommendations. Additionally, businesses should invest in upskilling employees to work alongside AI, equipping them with the knowledge and confidence to learn to leverage AI-driven tools effectively.

In summary

AI’s potential is undeniable, but businesses must cut through the hype and invest in strategic, value-driven AI solutions. Successful implementation requires aligning AI with clear business objectives, ensuring seamless data and workflow integration, and maintaining rigorous security standards.

When evaluating vendors, it would be prudent to seek technology providers that develop AI to solve real business challenges, delivering practical, responsible and results-driven capabilities. The companies that will thrive are those that thoughtfully integrate AI into their operations to enhance decision-making, streamline operations, and drive measurable growth.

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