Five Tips To Maximize AI Value For Your Business

AI is already reshaping how mid-market organizations operate, with over half now using it in their daily business processes. Companies that want to stay competitive can’t afford to wait, with 85% worrying they’ll fall behind. Mid-market leaders are fighting this concern with increased budgets, hoping to see up to four times their AI investments by late 2025.

To capture AI’s transformative value, companies need to focus on the foundational moves that make it work at scale across their entire organization. 52% of organizations are already establishing dedicated teams to drive generative AI adoption. For those preparing their systems for widespread AI implementation, they must focus on upgrading tech infrastructure, streamlining data workflows, and enhancing cybersecurity. Pairing AI with user-friendly low-code technologies can also help streamline operations and boost efficiency throughout teams.

Done right, these steps not only prepare companies to support AI workloads, but they also protect employees, ensure data reliability, and set the stage for better teamwork, faster service, and stronger customer relationships.

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Here are five tips for how organizations can effectively implement AI:

1. Build a modern infrastructure

Organizations should begin by evaluating their current infrastructure and prioritizing upgrades that enable migration to scalable, cloud-native platforms built for AI. Adopting these technologies can support heavier AI workloads while enhancing agility, performance, and cost-effectiveness. Strengthening cloud capabilities and removing outdated on-prem solutions also adds a layer of security and resilience, helping to meet today’s advanced security demands.

2. Make data your differentiator

Clean, organized data is essential for AI success. Companies should streamline their systems to increase accuracy and efficiency. Setting up unified analytics helps generate better insights, and embedding AI into data processes can also accelerate decision-making while extending access to the entire organization.

Ultimately, the effectiveness of any AI measure will depend on the quality of the data behind it. To deliver fast and reliable outcomes for customers and teams, organizations need accurate, well-managed data. They should prioritize routine data validation and cleansing to uphold precision and implement strong data governance practices to build trust in both their data and AI systems.

3. Fortify security from the start

The benefits AI can provide grow every day, but so do security threats. 93% of mid-market organizations cite gaps in their security, data protection, or threat defense as hindering their AI adoption. Implementing adaptable, AI-ready security frameworks that evolve with emerging threats can help build a strong foundation for success. This includes embedding AI into threat detection and incident response to identify risks faster and respond more effectively.

These AI efforts should be integrated within an organization’s broader IT and cybersecurity strategies. Organizations must foster close collaboration between security and IT teams to ensure cohesive planning and execution. An important step is also to enforce role-based access controls, to ensure that employees have the right permissions at the right time, establishing safeguards that prevent accidental data exposure or misuse. Focusing on ethical AI use and responsible automation can also help maintain trust while facilitating new capabilities.

4. Boost productivity with smart automation

Organizations should identify areas where AI can drive the most impact, from automating repetitive tasks to optimizing workflows and reducing operational costs. AI agents can be deployed across key roles and systems to enhance responsiveness. By simplifying processes and eliminating bottlenecks, teams can focus on higher-value work and have a better employee experience. Companies need to invest in AI-enhanced applications and train employees to work effectively with these intelligent systems, as 48% of employees say formal training would make them more confident in using gen AI tools. This not only boosts productivity but also improves teamwork and speeds up innovation.

5. Accelerate value with low-code tools

Low-code platforms offer a fast path to building custom applications that extend the value of existing systems. By layering new capabilities onto core workflows, organizations can close process gaps and better align technology with business needs. Transitioning core applications to evergreen cloud solutions ensures access to the latest innovations in AI and automation. Using low-code tools to connect fragmented processes also helps reduce friction and improve operational flow across the organization.

By focusing on these fundamental steps, mid-market organizations can unlock AI’s full potential more quickly. From infrastructure to development tools, each investment strengthens their ability to scale innovation, improve performance, and stay competitive in a world increasingly shaped by AI.

About The Author Of This Article

Gord Mawhinney is President of the Americas at Avanade

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