Winning in 2026: 10 practical priorities for business leaders in the age of AI

Business leaders heading into 2026 face a simple choice: treat AI and digitalisation as buzzwords, or turn them into concrete advantages in productivity, customer experience and growth.

In Ghana, where digital transformation could unlock tens of billions of cedis in value by 2029, the most successful leaders will be those who apply global lessons locally and move decisively, even with constrained resources.​​

Move from AI experiments to a few scaled use cases

In 2025, most organisations globally used AI somewhere, but only about a third had scaled it across the enterprise, and high performers stood out by focusing on a handful of high‑value use cases and driving them to scale. In Ghanaian businesses, common early wins include AI for sales forecasting, credit risk, customer support chatbots, and basic process automation in finance and operations.​​

For 2026, choose two or three use cases that directly impact revenue or cost – for example, demand forecasting in retail, yield prediction in agriculture, or collections optimisation in financial services – and commit to making them part of standard workflows, not side pilots. Define clear success metrics (e.g., stock‑outs reduced, non‑performing loans decreased) and review them monthly so AI value becomes visible and trusted.​​

Treat AI as a growth and innovation engine, not only a cost lever

High‑performing AI organisations were more likely in 2025 to set growth and innovation goals, not just efficiency targets, and they reported stronger gains in revenue, customer satisfaction and market share. Ghanaian companies can do the same by using AI to launch new digital services, enter regional markets, or offer personalised products – such as tailored lending products, value‑added services for farmers, or 24‑hour digital customer support.​​

Anchor AI initiatives to concrete growth questions: “How can we reach new customer segments?”, “How can we sell more to existing customers?”, “What new service can we deliver digitally at low marginal cost?”. This mindset helps attract investment approval internally and positions the business for regional competitiveness rather than a defensive posture.​​

Redesign workflows around AI, not the other way round

One of the strongest predictors of AI success in 2025 was whether organisations fundamentally redesigned workflows to incorporate AI, rather than simply dropping tools into old processes. High performers were almost three times more likely to do this and to embed AI into day‑to‑day operations with clear roles for people and systems.​

In practical terms, a Ghanaian bank implementing an AI risk model should redesign credit approval steps, responsibilities and checks – not just add a scoring screen on top of the old manual process. A logistics company using AI for routing should redefine dispatcher tasks, driver communication and exception handling so AI recommendations become the default starting point, not an optional add‑on.​​

Build “human‑in‑the‑loop” trust and governance

Inaccuracy and explainability were among the most common AI‑related risks experienced in 2025, and leading companies responded by creating clear rules on when humans must review AI outputs. High performers were significantly more likely to define these human‑in‑the‑loop processes and to coordinate AI efforts centrally so risks and learnings could be shared.​

For Ghanaian businesses, this means deciding, for each AI use case, thresholds and scenarios where human review is mandatory – for example, high‑value loans, regulatory‑sensitive decisions, or customer communications in dispute situations. It also means assigning a cross‑functional group (IT, business, risk, legal) to oversee AI models, monitor performance, and update policies in line with emerging national AI guidelines.​​

 Invest in data quality and small, reusable data products

2025 evidence shows that organisations capturing the most value from AI have invested in robust data infrastructure and reusable “data products” that can feed multiple use cases. In Ghana, where data is often fragmented across manual records, spreadsheets and unconnected systems, the priority is not “big data” but “fit‑for‑purpose data” that is accurate, timely and well‑structured.​​

Start by identifying a few critical data domains that underpin your chosen AI use cases – for instance, customer transaction histories, farm‑level production data or logistics delivery records – and standardise how they are collected and stored. Over time, package these into internal data sets (e.g., “SME credit history”, “cocoa supply volumes”) that can be reused across analytics and AI projects, reducing cost and lead time.​​

Close the skills gap with targeted upskilling, not only hiring

Larger organisations globally were more likely to hire AI data scientists, engineers and product owners in 2025, but many still struggled with skills gaps and change‑management challenges. Ghanaian SMEs, constrained by budgets, cannot rely solely on expensive specialist hires; they need to blend modest hiring with focused upskilling of existing staff and smart use of cloud tools.​​

Practical moves include training finance teams on AI‑driven forecasting dashboards, coaching sales teams on AI‑assisted CRM tools, and building a cohort of “AI champions” who understand both business and technology. Where possible, leverage local universities, tech hubs and online programmes to develop AI literacy across the workforce, not just in IT.​​

Strengthen digital and AI strategy around Ghana’s policy direction

Ghana’s digital and AI policy frameworks – including digital economy strategies and practitioner guides – aim to foster inclusive, responsible AI that supports national development priorities in sectors like agriculture, manufacturing and financial inclusion. Aligning corporate strategies with this direction can unlock partnerships, funding and regulatory goodwill.​

In 2026, leaders should map how their AI and digital initiatives contribute to national goals such as job creation, SME empowerment, rural inclusion and a 24‑hour digital economy. This can mean, for example, designing AI solutions that work on low‑cost devices, supporting local language interfaces, or partnering with government and development agencies on sector‑specific pilots.​

Use AI and digital tools to make supply chains shock‑resilient

Global trends in 2025 showed that AI‑enabled supply chain visibility, forecasting and scenario planning are becoming standard tools for managing climate, geopolitical and market volatility. For Ghanaian firms exposed to commodity price swings, port delays and currency fluctuations, these tools can be the difference between margins eroding and margins stabilising.​

In 2026, consider AI‑enhanced demand and inventory planning, early‑warning dashboards for supply disruptions, and dynamic pricing or sourcing strategies that adjust as conditions change. Even simple steps – such as digitising supplier records, tracking delivery times, and using predictive analytics for stock levels – can significantly improve resilience for SMEs.​

Design AI and digital initiatives for inclusivity and trust

Across Africa, digital adoption is expected to contribute a growing share of GDP, but only if solutions are inclusive and address barriers such as device affordability, connectivity gaps and skills disparities. Ghana’s AI and digital strategies explicitly emphasise ethical, inclusive deployment and the need to protect privacy, fairness and security.​

For businesses, that translates into designing products and processes that work for low‑income, rural and informal customers, using local languages where possible and ensuring transparent communication when AI is involved in decisions. Building trust also requires visible commitments to data protection, responsible marketing and clear grievance channels when customers feel disadvantaged by algorithm‑driven outcomes.​

 Lead from the top with clear vision, KPIs and courage

Survey data from 2025 shows that AI high performers almost always have senior leaders who actively champion AI, understand where it creates value, and stay engaged beyond the initial launch. They also invest more heavily, dedicate cross‑functional teams, and hold themselves accountable for measurable outcomes like EBIT impact, innovation metrics and customer satisfaction.​

In Ghanaian organisations, leaders should articulate a simple, compelling AI and digital vision – for example, “to become the most data‑driven bank for SMEs” or “to build Ghana’s most efficient digital supply chain for agribusiness” – and tie incentives to progress. Above all, 2026 will reward leaders who are willing to experiment, learn from pilots, admit what is not working, and keep pushing until AI and digital tools are embedded in the fabric of how their organisations operate.

Wrapping Up

The choices leaders make now about where to focus, how boldly to experiment, and how inclusively to deploy technology, will determine which organisations simply survive and which help shape a more prosperous, resilient economy for everyone.

Wishing you and your teams clarity, courage and sustained success in the new year as you turn these priorities into real impact in your businesses and communities. May 2026 meet Ghanaian and African businesses at a moment of renewed confidence, with growth, digitalisation and AI all moving from promise to tangible progress.

 Dr. Gillian Hammah is the Chief Marketing Officer at Aya Data, a UK & Ghana-based AI consulting firm, that helps businesses seeking to leverage AI with data collection, data annotation, and building and deploying custom AI models. Connect with her at gillian@ayadata.ai or  www.ayadata.ai