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Quest Training

AI Use Cases & Business Value Realization Training Course

Helps organizations find valuable AI use cases, weigh feasibility and benefits, prioritize investments and plan delivery that yields measurable business value.

AIEA · Artificial Intelligence & Enterprise ApplicationsAll Levels#2739ClassroomEnglish , Arabic
Duration
5 Days
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Free substitution at any time · 30+ days' notice: full refund minus 10%. Cancellation policy

Sectors:Data, Analytics & Digital TransformationCategories:Artificial Intelligence & Enterprise Applications

Course Overview

This course equips participants with practical methods for identifying high-value artificial intelligence (AI) use cases and translating them into measurable business outcomes. It focuses on aligning AI initiatives with organizational priorities, evaluating feasibility and expected benefits, prioritizing investment opportunities, and developing implementation plans that deliver tangible operational and strategic value. Participants explore AI applications across business functions, including process automation, customer experience, decision support, predictive analytics, and operational optimization. The programme also covers business case development, return on investment (ROI), performance measurement, risk assessment, and value realization, enabling organizations to move from AI experimentation to scalable, results-driven implementation.

Learning Objectives

  • By the end of the course, participants will be able to:
  • Identify AI use cases aligned with organizational strategy and business priorities.
  • Evaluate opportunities for AI adoption across operational and support functions.
  • Assess the technical feasibility, business impact, and implementation requirements of proposed AI initiatives.
  • Prioritize AI use cases according to business value, cost, complexity, risk, and organizational readiness.
  • Develop business cases that quantify expected benefits, investment requirements, and implementation costs.
  • Estimate financial and operational returns using appropriate ROI and value assessment methods.
  • Define measurable key performance indicators (KPIs) for AI initiatives.
  • Identify data availability, quality, integration, and governance requirements for AI implementation.
  • Evaluate ethical, regulatory, security, and operational risks associated with AI use cases.
  • Develop implementation roadmaps that support adoption, performance monitoring, and sustainable value realization.

Who Should Attend

This course is designed for business leaders, department heads, strategy managers, digital transformation professionals, AI programme managers, business analysts, and innovation leaders responsible for identifying, evaluating, or overseeing AI initiatives. It is particularly valuable for professionals seeking to connect AI capabilities with measurable improvements in productivity, service delivery, decision-making, cost efficiency, and organizational performance. The programme is also suitable for IT managers, data and analytics leaders, project and portfolio managers, finance professionals, and operational excellence specialists in government entities, ministries, banks, financial institutions, oil and gas companies, industrial organizations, and large corporations. Participants do not need advanced AI programming skills, although familiarity with business processes, performance management, or digital transformation initiatives is beneficial.

Learning Outcomes

  • Map organizational challenges and strategic objectives to relevant AI opportunities.
  • Develop a structured inventory of potential AI use cases across business functions.
  • Distinguish between automation, predictive analytics, generative AI, and other AI application patterns.
  • Evaluate AI opportunities using business value, feasibility, risk, and readiness criteria.
  • Prepare business cases with clear assumptions, cost estimates, expected benefits, and investment requirements.
  • Calculate and interpret ROI, payback period, and other relevant financial evaluation measures.
  • Define KPIs and baseline measurements to track AI initiative performance.
  • Identify data, technology, skills, governance, and change management requirements.
  • Establish controls for AI risks, responsible use, security, and regulatory compliance.
  • Create a phased roadmap for piloting, implementing, scaling, and monitoring AI initiatives.

Course Outline

Day 1

AI Business Opportunities and Strategic Alignment

  • Understanding the role of AI in business transformation and organizational performance.
  • Reviewing AI capabilities, including machine learning, predictive analytics, natural language processing, computer vision, and generative AI.
  • Identifying business challenges that can be addressed through AI-enabled solutions.
  • Mapping AI opportunities to strategic objectives, operational priorities, and service improvement targets.
  • Exploring AI applications in finance, human resources, customer service, procurement, operations, risk management, and reporting.
  • Distinguishing AI use cases from conventional automation and standard digital solutions.
  • Understanding the importance of process maturity, data readiness, and stakeholder alignment.
  • Developing an initial inventory of AI opportunities across departments.
  • Practical Exercise: Identify and document potential AI use cases for a selected organization, linking each opportunity to a defined business challenge and expected outcome.
Day 2

AI Use Case Identification, Assessment, and Prioritization

  • Applying structured techniques to discover and define AI use cases.
  • Mapping business processes to identify inefficiencies, bottlenecks, and opportunities for intelligent automation.
  • Assessing potential benefits, including productivity gains, cost reduction, service quality, risk reduction, and revenue improvement.
  • Evaluating technical feasibility, data availability, integration complexity, and infrastructure requirements.
  • Assessing organizational readiness, workforce capabilities, and change requirements.
  • Applying value-versus-effort matrices and weighted scoring models to prioritize opportunities.
  • Evaluating dependencies, implementation risks, and constraints.
  • Distinguishing quick wins from strategic, longer-term AI initiatives.
  • Practical Exercise: Develop a prioritized AI use case portfolio using business value, feasibility, risk, cost, and readiness criteria.
Day 3

Business Case Development and Financial Value Assessment

  • Structuring a business case for an AI initiative.
  • Defining the business problem, proposed solution, scope, assumptions, and expected outcomes.
  • Estimating implementation costs, including technology, infrastructure, data preparation, integration, training, and ongoing operations.
  • Quantifying tangible benefits such as labor efficiency, reduced processing time, fewer errors, and lower operating costs.
  • Assessing intangible benefits, including improved customer experience, decision quality, agility, and organizational knowledge.
  • Calculating return on investment, payback period, and other relevant financial measures.
  • Conducting sensitivity analysis and evaluating alternative implementation scenarios.
  • Identifying benefit owners and establishing accountability for expected results.
  • Practical Exercise: Prepare a business case for a selected AI use case, including cost estimates, benefit assumptions, financial evaluation, risks, and implementation considerations.
Day 4

Implementation Planning, Governance, and Performance Measurement

  • Translating prioritized AI use cases into pilot and implementation plans.
  • Defining project scope, deliverables, milestones, responsibilities, and resource requirements.
  • Assessing data quality, availability, accessibility, privacy, and integration needs.
  • Establishing governance arrangements for AI development, deployment, and ongoing oversight.
  • Evaluating ethical considerations, bias, transparency, security, and regulatory requirements.
  • Defining baseline performance measures and KPIs for business and operational outcomes.
  • Establishing monitoring mechanisms for accuracy, reliability, adoption, cost, and business impact.
  • Managing stakeholder engagement, workforce readiness, and organizational change.
  • Practical Exercise: Develop an AI implementation plan with governance controls, risk mitigation measures, performance indicators, and defined responsibilities.
Day 5

Business Value Realization, Scaling, and Continuous Improvement

  • Understanding the stages of AI value realization from experimentation to operational deployment.
  • Establishing benefit realization plans and mechanisms for tracking expected versus actual outcomes.
  • Evaluating pilot results against predefined business objectives and performance baselines.
  • Identifying reasons for value gaps, including adoption barriers, data limitations, process weaknesses, and inaccurate assumptions.
  • Developing strategies for scaling successful AI use cases across departments and business units.
  • Establishing ongoing performance reviews and mechanisms for continuous improvement.
  • Evaluating the sustainability of AI investments and the need for model, process, or technology updates.
  • Integrating AI initiatives into portfolio management, strategic planning, and performance reporting.
  • Final Workshop: Develop and present an AI value realization roadmap covering prioritized use cases, business cases, investment assumptions, implementation phases, governance requirements, KPIs, and benefit tracking mechanisms.

Upcoming Dates

Selected date

Vienna · 15 – 19 Feb 2027 · Classroom

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CityDatesPrice per ParticipantEarly Bird
KigaliScheduled
2 – 6 Nov 2026€5,100—
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Kuala LumpurScheduled
9 – 13 Nov 2026€4,400—
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LisbonScheduled
16 – 20 Nov 2026€5,400—
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LondonScheduled
23 – 27 Nov 2026€5,600€5,040until 2 Nov
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MadinahScheduled
30 Nov – 4 Dec 2026€4,200€3,780until 9 Nov
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MadridScheduled
7 – 11 Dec 2026€5,400€4,860until 16 Nov
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MarbellaScheduled
14 – 18 Dec 2026€5,400€4,860until 23 Nov
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ManamaScheduled
14 – 18 Dec 2026€4,700€4,230until 23 Nov
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MarrakeshScheduled
21 – 25 Dec 2026€4,300€3,870until 30 Nov
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MilanScheduled
28 Dec 2026 – 1 Jan 2027€6,000€5,400until 7 Dec
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MuscatScheduled
4 – 8 Jan 2027€5,300€4,770until 14 Dec
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OnlineScheduled
10 – 14 Jan 2027€1,700€1,530until 21 Dec
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ParisScheduled
18 – 22 Jan 2027€5,700€5,130until 28 Dec
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RomeScheduled
25 – 29 Jan 2027€5,800€5,220until 4 Jan
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RiyadhScheduled
25 – 29 Jan 2027€4,200€3,780until 4 Jan
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SalalahScheduled
1 – 5 Feb 2027€5,300€4,770until 11 Jan
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Sharm El-SheikhScheduled
8 – 12 Feb 2027€4,300€3,870until 18 Jan
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ViennaScheduled
15 – 19 Feb 2027€5,700€5,130until 25 Jan
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AbujaScheduled
22 – 26 Feb 2027€5,100€4,590until 1 Feb
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AccraScheduled
1 – 5 Mar 2027€5,100€4,590until 8 Feb
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AmsterdamScheduled
8 – 12 Mar 2027€5,400€4,860until 15 Feb
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BarcelonaScheduled
15 – 19 Mar 2027€5,400€4,860until 22 Feb
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CairoScheduled
15 – 19 Mar 2027€3,300€2,970until 22 Feb
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CasablancaScheduled
22 – 26 Mar 2027€4,300€3,870until 1 Mar
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DohaScheduled
29 Mar – 2 Apr 2027€4,400€3,960until 8 Mar
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DubaiScheduled
4 – 8 Apr 2027€4,400€3,960until 15 Mar
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GenevaScheduled
12 – 16 Apr 2027€6,300€5,670until 22 Mar
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HamburgScheduled
19 – 23 Apr 2027€5,800€5,220until 29 Mar
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IstanbulScheduled
26 – 30 Apr 2027€4,700€4,230until 5 Apr
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JeddahScheduled
2 – 6 May 2027€4,200€3,780until 12 Apr
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Available in: Istanbul · Dubai · London · Riyadh · Doha · Amsterdam

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