• Sixbert SANGWA
• Thadee Gatera
• Simeon Nsabiyumva
• Isaac Museveni
• Placide Mutabazi

The accelerating proliferation of artificial-intelligence (AI) applications has left professionals, consultants, and policy-makers grappling with a fragmented landscape of tools whose value is rarely mapped to the precise tasks they perform. This study answers that gap by constructing the first universal, two-tier Task–Tool Matrix that links more than 1,000 contemporary AI solutions to both (i) cross-cutting business functions—administration, HR, finance, marketing, customer service, analytics, IT, and legal—and (ii) sector-specific activities in healthcare, manufacturing, education, retail, agriculture, logistics, and the public sector. Employing a mixed-methods design, we blended systematic scraping of public directories, expert validation interviews (n = 27), and comparative benchmarking of performance, cost, and integration complexity. The resulting database feeds a five-stage Recommendation Framework—task analysis, candidate identification, multi-criteria evaluation, pilot testing, and scaled deployment—that can be operationalised as a searchable API or decision-support dashboard. Case-study simulations across four industries demonstrate the framework’s capacity to cut tool-selection time by 65 %, reduce implementation costs by 28 %, and improve task accuracy by up to 19 % compared with ad-hoc approaches. Beyond immediate consultancy utility, the matrix reveals macro-patterns: administrative automation remains the low-hanging fruit (63 % of mapped use cases), while predictive maintenance and generative design signal the next wave of industrial AI. A forward-looking horizon scan identifies emergent gaps—explainable AI for regulated sectors, interoperable multi-agent orchestration, and low-resource-language support—that are poised to shape the ecosystem over the next decade. By translating the sprawling AI marketplace into a rigorously validated, task-centric roadmap, this paper equips organisations of all sizes to pursue evidence-based, ethically aligned, and ROI-positive AI adoption, thereby accelerating inclusive digital transformation across the global economy.

AI consultancy, task-tool mapping, industry-specific AI tools, cross-sector automation, AI adoption framework, digital transformation strategy, future of work

"Mapping AI Tools to Global Industry Tasks: A Universal Framework for AI Consultancy & Adoption", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 7, page no.a741-a778, July-2025, Available :http://www.jetir.org/papers/JETIR2507077.pdf

"Mapping AI Tools to Global Industry Tasks: A Universal Framework for AI Consultancy & Adoption", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 7, page no. ppa741-a778, July-2025, Available at : http://www.jetir.org/papers/JETIR2507077.pdf