Best AI Training for BFSI, NBFC and Insurance Companies in ABU DHABI

Best AI Training for BFSI, NBFC and Insurance Companies in Abu Dhabi: Lead Generation, Follow-Up and CRM Productivity

Best AI Training for BFSI, NBFC and Insurance Companies in ABU DHABI

Abu Dhabi has never treated progress as a temporary trend.

The emirate brings together heritage, discipline and long-term vision. The serenity of the Sheikh Zayed Grand Mosque, the intellectual grandeur of Qasr Al Watan, the cultural ambition of Saadiyat Island, the energy of Yas Island, the timeless oasis of Al Ain and the open dunes of Liwa all communicate the same lesson: meaningful transformation is built carefully, responsibly and for the long term.

That lesson now applies directly to banking, financial services, NBFCs, insurance companies, wealth-management firms and fintech organisations.

Artificial intelligence is no longer optional. It is becoming a decisive advantage in competitive positioning, risk management, compliance, customer experience, fraud identification, product development and operational efficiency.

The institutions that develop responsible AI capabilities today will be better equipped to serve customers tomorrow. Those that delay adoption may find themselves competing against organisations that can research markets, prepare proposals, analyse customer needs, document decisions and complete follow-ups in a fraction of the time.

Why Abu Dhabi’s Financial Sector Needs Practical AI Training

The financial-services industry does not need another motivational presentation about the future of AI.

It needs employees who know:

• What information can safely be entered into an AI platform.

• How to create reliable prompts without disclosing customer data.

• How to draft compliant communications without making unapproved claims.

• How to analyse CRM and operational data without exposing personally identifiable information.

• How to verify AI-generated calculations, summaries and recommendations.

• When human approval is mandatory.

• How to document AI-assisted decisions for review and audit.

This distinction is particularly important in the UAE.

In February 2026, the Central Bank of the UAE issued guidance concerning consumer protection and the responsible adoption of artificial intelligence by licensed financial institutions, including insurance providers. The framework addresses governance, accountability, fairness, transparency, explainability, data quality, privacy, security, continuous monitoring, human oversight and consumer protection.

The UAE’s personal-data protection framework also establishes controls and organisational responsibilities for processing and securing personal information. For a bank, NBFC or insurer, AI adoption must therefore begin with governance—not with unrestricted experimentation.

From AI Awareness to Measurable Business Productivity

A valuable BFSI AI programme must connect tools to real work.

Parikshit Khanna’s training methodology focuses on the daily responsibilities of CEOs, CXOs, vice presidents, branch leaders, relationship managers, sales teams, risk professionals, claims teams, finance departments, operations units and customer-service executives.

Participants do not simply watch tool demonstrations. They work through controlled, role-specific scenarios and build reusable frameworks for their departments.

1. Lead Generation and Market Opportunity Identification

AI can help financial organisations identify and prioritise market opportunities without replacing human judgement.

Training use cases can include:

• Creating ideal customer profiles for retail, SME, HNI and corporate segments.

• Analysing anonymised customer patterns to identify service opportunities.

• Preparing industry-specific outreach strategies.

• Creating personalised introductory emails and WhatsApp drafts.

• Developing branch-level lead-generation campaigns.

• Drafting webinar, seminar and financial-awareness campaign concepts.

• Preparing referral-request communications.

• Converting research reports into concise opportunity briefs.

• Developing Arabic and English communication drafts for local review.

• Creating question banks for initial customer discovery calls.

The purpose is not to generate more messages indiscriminately. The purpose is to produce more relevant, respectful and customer-focused communication.

2. Faster and More Consistent Lead Follow-Up

Many valuable leads are lost not because the product is unsuitable, but because the follow-up process is delayed, inconsistent or generic.

AI-assisted follow-up systems can help employees:

• Summarise the customer’s previous conversation.

• Identify unresolved questions.

• Draft the appropriate next response.

• Prepare a document checklist.

• Create a follow-up schedule.

• Draft meeting-confirmation messages.

• Generate polite reminders without sounding aggressive.

• Prepare post-meeting summaries.

• Escalate high-intent opportunities to the appropriate manager.

• Draft renewal, maturity, premium and documentation reminders.

Every message should remain subject to approved templates, compliance requirements and human review.

3. CRM Productivity for Sales and Relationship Teams

A CRM becomes valuable only when its records are complete, current and actionable.

Practical AI training can show employees how to transform unstructured notes into controlled CRM updates, including:

• Customer requirement summaries.

• Meeting outcomes.

• Next-action recommendations.

• Follow-up dates.

• Product-interest categories.

• Document-status updates.

• Objection summaries.

• Lead-priority indicators.

• Renewal or review reminders.

• Escalation notes for supervisors.

AI can also help managers create anonymised pipeline narratives, branch summaries and review-meeting agendas from approved CRM exports.

The final update should always be verified by the responsible employee before being entered into the CRM.

Accelerating Time-to-Market for Financial Products

Accelerating the time-to-market for new products requires rapid market alignment, regulatory awareness, technical documentation and coordination across multiple departments.

AI can support—not replace—this process.

Market Trend Synthesis

Microsoft Copilot, ChatGPT, Claude and other approved enterprise platforms can help authorised teams organise industry reports, consumer-behaviour information and competitive intelligence into structured market-entry briefs.

A carefully designed workflow can produce:

• Market need summaries.

• Customer segment descriptions.

• Competitor comparison frameworks.

• Product opportunity maps.

• Distribution-channel assessments.

• Customer objection forecasts.

• Risk and assumption registers.

• Questions requiring legal or compliance review.

• Management presentation outlines.

• Pilot-market recommendations.

Employees must verify the original sources and distinguish established facts from AI-generated interpretations.

Product Documentation

AI can help product, operations and technology teams convert approved specifications, policy notes, process diagrams and architectural information into readable first drafts of:

• Product requirement documents.

• Standard operating procedures.

• User manuals.

• Internal process guides.

• Sales enablement documents.

• Product FAQs.

• Customer onboarding instructions.

• Training manuals.

• Release notes.

• Troubleshooting documents.

• Help-centre articles.

Raw technical resolutions and internal FAQs can also be transformed into clearer public-facing support articles after security, legal and compliance review.

Meeting Intelligence and Action Tracking

With properly configured enterprise tools, meeting transcripts can be converted into:

• Decisions taken.

• Outstanding questions.

• Clear action items.

• Proposed owners.

• Target dates.

• Risk points.

• Required approvals.

• Follow-up emails.

• Management summaries.

• CRM-ready notes.

Owner assignments generated by AI should be treated as recommendations. A responsible manager must confirm accountability before tasks are distributed.

AI Applications Across BFSI, NBFC and Insurance Functions

Function	Practical AI Applications
Leadership and Strategy	Board briefs, market synthesis, scenario planning, competitor analysis and decision memos
Sales and Distribution	Lead qualification, meeting preparation, follow-up drafts, proposal personalisation and CRM updates
Customer Service	FAQ drafting, response standardisation, complaint classification and escalation summaries
Credit and Lending	Document checklists, case-note structuring, exception summaries and review-question generation
Risk Management	Risk-register drafting, policy comparison, control mapping and incident-summary preparation
Compliance	Circular summaries, obligation trackers, policy drafts and review checklists
Insurance Underwriting	Submission summaries, information-gap identification and structured review notes
Claims	Document categorisation, chronology preparation, missing-information identification and communication drafts
Finance and FP&A	Variance narratives, management summaries, forecasting assumptions and reporting support
Operations	SOP development, process documentation, bottleneck analysis and escalation drafting
Human Resources	Job descriptions, training plans, interview questions and employee communication
Marketing	Campaign concepts, educational content, customer-segment messaging and presentation support
Product and Technology	Requirement documents, test scenarios, release notes, user manuals and help-centre content

AI-generated outputs must not be used as autonomous credit, underwriting, claims, compliance or investment decisions without appropriate governance, validation and human accountability.

Data Security First: The Foundation of BFSI AI Adoption

For financial institutions, the most important AI skill is not prompt writing.

It is knowing what must never be placed inside an unapproved AI system.

A responsible training programme should explicitly prohibit employees from experimenting with:

• Customer names and contact information.

• Emirates ID or passport details.

• Bank account and card numbers.

• Login credentials.

• KYC documentation.

• Credit reports.

• Medical or claims records.

• Policyholder information.

• Confidential pricing.

• Unpublished financial statements.

• Internal investigation material.

• Proprietary risk models.

• Employee-sensitive information.

• Regulator correspondence.

• Confidential contracts.

Parikshit Khanna’s Seven-Layer Secure AI Framework

Layer 1: Data Classification

Employees learn to classify information as public, internal, confidential, restricted or regulated before using any AI platform.

Layer 2: Approved Tools and Accounts

Business information should be processed only through organisation-approved accounts and configurations—not through unapproved personal accounts.

Layer 3: Anonymisation and Minimisation

Training exercises use fictional, synthetic, masked or anonymised information. Only the minimum necessary context is provided.

Layer 4: Permission-Based Access

AI should respect existing document and user permissions. Microsoft states that Microsoft 365 Copilot surfaces organisational information according to users’ underlying permissions and that prompts, responses and Microsoft Graph data are not used to train the foundation models powering Microsoft 365 Copilot.

Layer 5: Human Verification

Every financial, legal, compliance, underwriting, claims or customer-facing output requires qualified human review.

Layer 6: Auditability

Organisations should maintain an approved-use-case register, prompt standards, review responsibilities, incident procedures and audit trails appropriate to the risk of each application.

Layer 7: Continuous Monitoring

AI systems, outputs and vendor arrangements must be reviewed continuously because models, features, subprocessors and data-handling conditions can change.

ChatGPT, Custom GPTs, Claude and Microsoft Copilot

Parikshit’s sessions explain not only how to use each platform, but also how to select the appropriate tool and configuration for a particular risk level.

ChatGPT

ChatGPT can support structured research, drafting, analysis, brainstorming, documentation, role-play and workflow design.

Enterprise training areas include:

• Prompt engineering.

• Project instructions.

• Controlled research.

• Financial communication drafts.

• Product-documentation workflows.

• Data-analysis assistance using anonymised information.

• Customer-persona development.

• Meeting and report structuring.

• Reusable department prompt libraries.

Custom GPTs

A Custom GPT can be configured around defined instructions, approved knowledge and specific output formats.

Possible controlled BFSI applications include:

• Policy navigation assistants.

• Employee FAQ assistants.

• Sales-coaching assistants.

• Product-information assistants.

• Compliance-checklist assistants.

• Customer-communication reviewers.

• SOP drafting assistants.

• Learning and development assistants.

A Custom GPT should not be treated as automatically secure merely because it is customised. Access, knowledge sources, retention, external actions, permissions and administrator controls must be reviewed.

Microsoft 365 Copilot

Microsoft 365 Copilot can work within Word, Excel, PowerPoint, Outlook, Teams and other Microsoft 365 environments. It can use organisational context that the individual user is authorised to access, making permissions hygiene and information architecture critical.

BFSI examples include:

• Summarising approved email threads.

• Preparing meeting recaps.

• Drafting follow-up communications.

• Converting documents into presentations.

• Producing Excel formula and analysis suggestions.

• Comparing policy documents.

• Preparing management-review narratives.

• Searching authorised organisational knowledge.

• Building controlled agents around approved data sources.

Claude Within Supported Copilot Experiences

Microsoft now supports Anthropic models in selected Microsoft 365 Copilot experiences and regions, subject to administrator settings and applicable contractual or data-processing conditions. Administrators can enable or restrict provider access for specified users and groups.

For sensitive financial environments, organisations should evaluate where the model processes data, which contractual terms apply and whether the configuration meets internal and regulatory requirements.

Claude as a Separate Enterprise Tool

Claude can be valuable for:

• Long-document analysis.

• Policy comparison.

• Structured reasoning.

• Detailed report preparation.

• Complex document summarisation.

• Product and technical documentation.

• Management briefing notes.

• Scenario evaluation.

Power BI

Power BI can support executive and operational dashboards for:

• Sales pipelines.

• Branch performance.

• Portfolio monitoring.

• Claims trends.

• Customer-service metrics.

• Product performance.

• Operational turnaround time.

• Risk and compliance indicators.

AI-generated observations must be reconciled with validated source data.

n8n and Workflow Automation

Controlled automation can support:

• Lead-routing workflows.

• Follow-up reminders.

• Document-status notifications.

• Internal approval requests.

• CRM task creation.

• Report distribution.

• Customer-onboarding coordination.

• Escalation workflows.

• Reconciliation support.

• Management-alert generation.

No automation should independently approve loans, reject customers, settle claims, alter financial records or send sensitive communications without authorised controls.

Why Parikshit Khanna Is the Preferred Choice for CEOs, CXOs, VPs and Banking Professionals

1. Business-First Training

The session begins with departmental problems, not with a catalogue of AI tools.

A CEO may need faster market intelligence. A vice president may need clearer review reports. A branch leader may need better follow-up discipline. A compliance officer may need structured obligation tracking. A relationship manager may need more relevant customer communication.

Each requirement is converted into a practical, controlled AI workflow.

2. Role-Based Prompt Engineering

Participants learn a structured method covering:

• Role.

• Business context.

• Approved source material.

• Exact task.

• Constraints.

• Required format.

• Verification requirements.

• Escalation conditions.

• Prohibited actions.

This is significantly more useful than collecting random prompts from the internet.

3. Live Workflow Development

Participants see workflows built during the programme, including:

• Lead follow-up systems.

• CRM note structures.

• Customer email frameworks.

• Product briefs.

• Meeting-action trackers.

• Policy-comparison templates.

• Risk-review prompts.

• Executive-summary formats.

• SOP and technical-documentation templates.

4. Data-Security Emphasis

Every tool demonstration is connected to data classification, anonymisation, permissions, verification and human accountability.

5. Leadership-to-Frontline Relevance

The programme can be customised for:

• Board and CXO roundtables.

• Vice presidents and functional heads.

• Branch and regional managers.

• Relationship and wealth managers.

• Insurance sales and claims teams.

• Compliance, audit and risk professionals.

• Finance and FP&A teams.

• Operations and customer-service departments.

• IT, data and information-security teams.

• HR and learning teams.

6. Practical Cross-Sector Experience

Financial institutions increasingly interact with healthcare, real estate, manufacturing, tourism, retail, logistics, education and government ecosystems.

Parikshit’s cross-sector training experience helps him build realistic examples for health insurance, property finance, manufacturing credit, travel insurance, retail finance, supply-chain lending and institutional banking.

7. Post-Training Adoption Support

Depending on the programme structure, the engagement can include:

• Department prompt libraries.

• Secure-AI checklists.

• Role-based exercises.

• Implementation roadmaps.

• Use-case prioritisation.

• Manager-review templates.

• Follow-up support.

• Internal AI-champion guidance.

The First Dedicated AI-in-Healthcare Trainer at IIT Delhi

According to Parikshit Khanna’s documented programme record, he was the first trainer to deliver a dedicated AI-in-Healthcare training session at IIT Delhi.

This was not a generic AI-awareness session. It focused on the practical application of ChatGPT and Generative AI for healthcare professionals, supported by demonstrations of multiple AI tools.

That healthcare experience is directly relevant to insurers, health-finance companies and BFSI organisations working with:

• Medical insurance.

• Claims documentation.

• Hospital networks.

• Healthcare financing.

• Wellness programmes.

• Provider communications.

• Customer education.

• Medical-document summarisation.

• Claims-service workflows.

Updated Professional Profile

Parikshit Khanna is the Founder of Digital Training Jet, an MSME/Udyam-registered training entity.

His updated professional profile states that he has trained and mentored 1,20,000+ professionals and learners through corporate programmes, healthcare sessions, institutions, government bodies, professional associations and business communities.

His principal skills include:

• Generative AI.

• ChatGPT.

• Custom GPTs.

• Claude.

• Microsoft Copilot.

• Gemini and Gems.

• Prompt engineering.

• Agentic AI.

• n8n automation.

• Power BI.

• Canva AI.

• AI-enabled digital marketing.

• Enterprise AI adoption.

• Data-security awareness.

• AI governance.

• Role-based productivity workflows.

• AI for healthcare.

• AI for BFSI.

• AI for manufacturing.

• AI for education.

• AI for tourism.

His portfolio materials present a proof-led approach, separating delivered engagements from scheduled sessions, active discussions and proposals—an important distinction that should remain intact when publishing client credentials.

Consolidated Client and Institutional Portfolio

The following list consolidates the organisations, institutions, professional bodies and engagement names supplied for this article and included in Parikshit Khanna’s current professional materials. Client permissions and the exact status of delivered, scheduled, partnership or proposal-based engagements should be checked before public publication.

Banking, Finance, NBFC, Investment and Insurance

Kae Capital, Tata Mutual Fund, AILifeBot, AON Consulting, Decyphr, Mastertrust Finance, Ambit Capital, Edelweiss, Chinmay Finlease Ahmedabad, Sudeep Group Vadodara, VISA, Niva Bupa Health Insurance, Bettering Results, Gaursons, County Group, CREDAI and City Homes Group.

Real Estate and Infrastructure

Gaurs Group, Gaur Sons, Gaursons India, County Group, City Homes Group, CREDAI, Homeland Group, Kanakia Group, Kanakia Spaces Realty, Tandon Urban Solutions and Designer Home & Landscapes.

Healthcare, Hospitals, Medical Associations and Pharmaceuticals

AIIMS Delhi, CARE Hospitals Hyderabad, Fortis, Santevita Hospital Ranchi, Cloud Nine Hospitals, Continental Hospitals, Dr Agarwal’s Eye Hospital, Surat Medical Consultants’ Association, Surat Medical Association, Surat Doctors Association, IMA Janakpuri, JPCON 2026, Indian Academy of Pediatrics–CMIC, Hetero Pharma, Hetero’s CDMA Team, NIPUNA Learning Academy, Naprod Life Sciences, USV Pharma, Wockhardt, Sudeep Pharma Limited Vadodara, Cepheid India, Teerthanker Mahaveer Dental College, Galgotias School of Nursing, IIT Guwahati SYNAPSE, IIT Delhi healthcare cohorts and medical, dental and clinician groups.

Universities, Colleges and Educational Institutions

IIT Delhi, IIT Hyderabad, IIT Guwahati, IIT Roorkee, BITS Pilani, NSRCEL at IIM Bangalore, Goldman Sachs 10,000 Women Programme, Chitkara College of Sales and Marketing, Chitkara University, Thapar University, IILM College Jaipur, SOIL School of Business Design, Masters’ Union, Princeton Academy, Amity University Online, GL Bajaj Institute of Management and Research, GL Bajaj Institute of Technology, Galgotias University, Christ University, FIIB New Delhi, Apeejay School of Management, Ram Lal Anand College, I.T.S. Paramedical College, I.T.S. Mohan Nagar, Gateway Education, GIET Sonipat, Accurate Group of Institutions, Gaurs International School and Teerthanker Mahaveer Dental College.

Government, Public Sector and National Institutions

Prasar Bharati, National Academy of Broadcasting and Multimedia, All India Radio and Doordarshan cohorts, Delhi Jal Board, Indian Army and affiliated audiences, and public-sector and institutional programmes.

Manufacturing, Energy, Industrial and Engineering

Tata Power and Tata Power Skill Development Institute, Sheela Foam, Sleepwell, Sangam Group, Bonfiglioli, Aries Agro Limited, Epiroc Mining India, Epiroc Innovation and Technology Center, Hero Future Energies, Sudeep Pharma Limited, Anubhav Apparels, Emami Limited, Pansari Group, VULKAN Technologies, Siemens, Wahluft, Lucrative Impex, IMECO India, Dekin Electronics, CP PLUS and industrial, plant, operations and skill-development cohorts.

Tourism, Travel and Hospitality

ATTOI Annual Convention 2025 in Wayanad, TBO Aerocity, TBO.com, The Travel Nexus, the Taj Amer Jaipur engagement and travel-agency, tourism and hospitality communities.

At ATTOI, Parikshit delivered a keynote on maximising marketing efficiency with ChatGPT, strengthening his positioning in practical AI for tourism businesses.

Retail, Lifestyle, Consumer and Enterprise Organisations

Arvind Fashions, Arvind Lifestyle Brands, Tommy Hilfiger, Calvin Klein, Landmark Group, Max Fashion, LG India, Malabar Group, METRO Global Solution Center, Philip Morris, Tata Group, ZAFCO, Team Computers, Micros IT Solutions, Micros Digital, AILABS, Data-Core, BeTheBee, Designer Home Solution, Designer Home & Landscapes, Innovations Global, Kubrii, CIPL, Ranchi Gymkhana Club, JITO Chennai, JITO Raipur, CII New Delhi, Shemaroo Entertainment and Business France.

Logistics and Supply Chain

Yusen Logistics, Seair Global, TBO and logistics, freight, documentation, operations and customer-service teams.

Legal and Professional Services

Bettering Results, legal-professional cohorts, Custom GPT programmes for lawyers, contract-review workflows and the wider Bar & Bench professional ecosystem.

AI Training Coverage Across the Abu Dhabi Emirate

Programmes can be planned for teams located throughout Abu Dhabi’s three principal municipal regions: Abu Dhabi City, Al Ain City and Al Dhafra.

The Department of Municipalities and Transport also identifies Zayed City, Al Mirfa, Liwa, Al Sila, Ghayathi and Delma within its Al Dhafra service coverage.

Offline, hybrid and online programmes can therefore be organised for organisations based in:

• Abu Dhabi City.

• Al Ain.

• Al Dhafra.

• Zayed City.

• Al Mirfa.

• Liwa.

• Al Sila.

• Ghayathi.

• Delma.

• Ruwais.

• Mussafah.

• Masdar City.

• Khalifa City.

• Mohammed Bin Zayed City.

• Yas Island.

• Saadiyat Island.

• Al Maryah Island.

• Al Reem Island.

• Al Shahama.

• Al Wathba.

• Al Raha.

• Sir Bani Yas Island and surrounding business or hospitality operations.

Al Ain’s oasis landscape represents continuity and intelligent resource management, while Al Dhafra connects desert, coast, heritage and geographically distributed communities. These qualities make localisation, accessibility and practical regional delivery especially important for enterprise training.

Comparison: Parikshit Khanna Versus a Generic AI Training Programme

Evaluation Area	Parikshit Khanna and Digital Training Jet	Generic Training Alternative
BFSI Orientation	Workflows for lead management, CRM, compliance, risk, finance, claims, documentation and leadership	Broad AI demonstrations with limited financial context
Data Security	Data classification, anonymisation, permissions, approved tools, human review and auditability	Basic warning not to share confidential information
Training Method	Live, role-based and built around actual departmental tasks	Lecture-led or feature-led
Leadership Relevance	Customised for CEOs, CXOs, VPs, functional heads and branch leaders	One standard programme for every participant
Tool Coverage	ChatGPT, Custom GPTs, Claude, Microsoft Copilot, Gemini, Power BI, n8n and Canva AI	Usually restricted to one or two general tools
Automation	Controlled workflows with approvals and human-in-the-loop checkpoints	Basic demonstrations without governance design
Sector Experience	BFSI, healthcare, pharma, manufacturing, government, tourism, education, retail and real estate	Narrow or purely technical exposure
Documentation	Product briefs, SOPs, manuals, FAQs, help-centre content and action trackers	Mostly content-writing examples
Adoption Focus	Reusable prompts, implementation roadmaps and department-specific frameworks	Information without structured implementation
India and Sovereign-AI Vision	Viksit Bharat, responsible Indian capability-building and reduced uncontrolled dependency	Primarily tool promotion
Abu Dhabi Relevance	UAE-oriented BFSI examples, privacy controls, CBUAE awareness and regional delivery	International examples without sufficient localisation

Sovereign AI, Viksit Bharat and Responsible Global Collaboration

As a proud Indian professional committed to the vision of Viksit Bharat, Parikshit Khanna promotes stronger domestic capabilities in AI, data governance, enterprise implementation and workforce development.

Sovereign AI does not require organisations to reject global innovation. It requires them to understand:

• Where their data is processed.

• Which provider is responsible for it.

• Which laws and contractual protections apply.

• Whether sensitive information leaves the approved environment.

• How access is controlled.

• Whether an alternative India-hosted or on-premises deployment is required.

• How dependence on a single platform can be reduced.

• How Indian expertise and infrastructure can be strengthened.

The same principles are relevant to financial organisations in Abu Dhabi seeking dependable, transparent and strategically controlled AI adoption.

Recommended Training Formats

Executive AI Roundtable

Audience: CEOs, board members, CXOs and business headsDuration: 90 minutes to three hoursFocus: AI strategy, opportunity selection, risk, governance, data security and executive decision-making

BFSI Practical Workshop

Audience: Sales, operations, finance, compliance, risk, service and relationship teamsDuration: Half day or full dayFocus: Live prompts, CRM productivity, documentation, follow-up, reporting and secure AI usage

Department-Based AI Programme

Audience: Multiple functional teamsDuration: Two to ten sessionsFocus: Separate use cases, assignments, prompt libraries and adoption plans for each department

AI Champions Programme

Audience: Selected managers and internal transformation leadersDuration: Multi-week cohortFocus: Use-case prioritisation, governance, internal support, workflow testing and measurable adoption

Custom Enterprise Programme

Audience: Large banks, insurers, NBFCs, fintechs and diversified groupsDuration: Designed around organisational requirementsFocus: Approved platforms, policies, data boundaries, role-specific workflows and implementation roadmaps

Frequently Asked Questions

Is this training suitable for employees without technical experience?

Yes. The sessions use straightforward business language and live demonstrations. Separate advanced modules can be created for IT, data, automation and information-security teams.

Does the programme cover ChatGPT and Custom GPTs?

Yes. It can cover prompt engineering, reusable projects, Custom GPT design, approved knowledge sources, workflow structures, verification and access-control considerations.

Is ChatGPT included inside Microsoft Copilot?

No. ChatGPT is a separate OpenAI product. Microsoft 365 Copilot can use OpenAI-operated models, but this should not be described as ChatGPT itself being included in Copilot.

Is Claude available through Microsoft Copilot?

Claude is available in supported Microsoft 365 Copilot experiences and configurations, subject to region, product capability, administrator settings and applicable data-processing terms.

Will real customer or financial data be used during the training?

No sensitive customer information should be used. Exercises should be completed with fictional, synthetic, masked or properly anonymised information.

Can the workshop cover insurance-specific processes?

Yes. Modules can be developed for underwriting support, claims-document structuring, policy communication, renewal follow-up, distribution productivity, customer service and internal documentation.

Can the workshop cover lead generation and CRM follow-up?

Yes. This is a central part of the programme. Participants can build controlled frameworks for lead research, meeting preparation, follow-up drafting, CRM notes, next-action planning and management review.

Is the training available in Al Ain and Al Dhafra?

Yes. Programmes can be planned online, offline or in hybrid format for teams across Abu Dhabi City, Al Ain, Al Dhafra and other major business locations within the emirate.

Does the programme provide legal, investment or regulatory advice?

No. AI training supports productivity, documentation and responsible implementation. Legal, regulatory, investment, underwriting, medical and compliance decisions must remain with authorised professionals.

Ready to Transform Your BFSI Team?

AI is becoming a career-defining capability for banking, NBFC, finance and insurance professionals.

The objective is not to replace experienced employees. It is to help them research faster, communicate more clearly, document decisions more consistently, follow up more effectively and use organisational knowledge more responsibly.

Whether you are:

• A CEO leading enterprise transformation.

• A CXO developing an AI roadmap.

• A vice president improving business productivity.

• A branch head strengthening lead conversion.

• A risk leader evaluating responsible AI.

• A compliance professional managing regulatory information.

• An insurance executive improving claims or distribution workflows.

• A relationship manager seeking better customer communication.

• An operations leader reducing documentation delays.

Parikshit Khanna can design a practical, secure and role-specific programme for your organisation.

Contact for Corporate AI Training

Parikshit Khanna Founder, Digital Training Jet AI Trainer,

Corporate Enablement Specialist and Prompt Engineer

Email: parikshitkhanna@digitaltrainingjet.com

Phone: +91 9997213177 / +91 8076250669

Website: parikshitkhanna.com

X: @ParikshitK_

Parikshit Khanna — empowering financial leaders to use AI securely, practically and confidently.

The future of banking will belong not to organisations that merely purchase AI tools, but to those that build the people, policies and discipline required to use them responsibly.