BEST CHATGPT FOR IT INFORMATION TECHNOLOGY COMPANIES IN THE EUROPE

Best ChatGPT Training for IT Information Technology Companies in Europe: Lead Generation, Follow-Up and CRM Productivity

BEST CHATGPT FOR IT INFORMATION TECHNOLOGY COMPANIES IN THE EUROPE

From London’s commercial ambition and Parisian creativity to Berlin’s engineering discipline, Amsterdam’s collaborative spirit, Zurich’s precision and Tallinn’s digital-first culture, Europe has always transformed ideas into institutions.

The next transformation is already underway.

For European information technology companies, artificial intelligence is no longer an experimental tool reserved for innovation teams. It is becoming a decisive capability for generating qualified leads, accelerating sales follow-ups, improving CRM discipline, producing technical documentation, supporting customers and bringing new products to market faster.

However, adopting AI successfully requires more than giving employees access to a chatbot.

European organizations need a secure, governed and measurable operating model combining ChatGPT, Custom GPTs, Microsoft 365 Copilot, Claude, Gemini, Power BI, CRM platforms and approved automation tools.

That is where practical enterprise AI training becomes essential.

AI Is No Longer Optional for European IT Companies

AI is rapidly becoming a competitive differentiator in:

• Lead generation and account research

• Sales qualification and pipeline management

• CRM data enrichment and hygiene

• Customer follow-up

• Product documentation

• Software development support

• Customer service

• Fraud and anomaly detection

• Risk management and compliance

• Regulatory reporting

• Knowledge management

• Personalized customer experiences

• Secure workflow automation

• Executive decision-making

The question is no longer whether an IT company should use AI. The real questions are:

Which tools should be used? Which information may be shared? Who should approve the output? How should AI connect with the CRM? How can productivity be improved without compromising customer data, intellectual property or regulatory obligations?

These questions are especially important in Europe, where organizations must consider the General Data Protection Regulation and the evolving requirements of the EU AI Act. The EU AI Act entered into force on August 1, 2024, while GDPR has applied since May 25, 2018.

ChatGPT, Microsoft Copilot and Claude: An Important Enterprise Accuracy Note

Microsoft 365 Copilot can use OpenAI GPT models, and Microsoft has also enabled Anthropic Claude models in selected Copilot experiences, subject to organizational settings, availability and regional conditions. In the EU, EFTA and United Kingdom, administrators can enable Anthropic models for certain experiences across Word, Excel and PowerPoint.

However, ChatGPT as a standalone product is not literally bundled inside Microsoft Copilot. Copilot can use OpenAI-operated or Microsoft-hosted GPT models, while ChatGPT remains a separate OpenAI product with its own workspace, administration and security controls.

This distinction matters for licensing, governance, data processing and employee training.

Microsoft also states that Anthropic models are currently excluded from the EU Data Boundary and certain in-country processing commitments. European organizations should therefore evaluate model-provider settings, data residency requirements and contractual terms before enabling third-party models for sensitive work.

How ChatGPT and Copilot Improve Lead Generation

Traditional lead generation often forces sales professionals to spend hours researching accounts, identifying decision-makers, reviewing industry developments and personalizing outreach.

A properly governed AI workflow can accelerate this process.

1. Ideal Customer Profile Development

ChatGPT or a Custom GPT can help teams convert historical customer information into structured ideal customer profiles based on:

• Industry

• Company size

• Technology environment

• Geography

• Business challenges

• Buying triggers

• Likely decision-makers

• Regulatory requirements

• Existing software stack

• Potential implementation barriers

The final targeting criteria should still be approved by sales leadership and checked for bias, accuracy and lawful use of personal data.

2. Account Research

Sales professionals can use approved AI tools to summarize publicly available company information, identify potential transformation priorities and prepare structured account briefs.

A useful account brief can include:

• Company overview

• Products and services

• Target customers

• Technology environment

• Recent strategic developments

• Probable operational challenges

• Potential AI use cases

• Relevant decision-making roles

• Suggested discovery questions

• Recommended outreach angle

3. Localized European Outreach

A single generic message will not connect equally well with technology leaders in London, Paris, Berlin, Madrid, Milan, Amsterdam, Stockholm or Warsaw.

AI can help sales teams adapt outreach according to:

• Country and language

• Industry terminology

• Buyer seniority

• Local market priorities

• Cultural communication preferences

• Regulatory context

• Product maturity

• Previous interactions

The objective is not to create artificial personalization. It is to produce communication that demonstrates genuine research and relevance.

4. Lead Qualification

AI-assisted qualification frameworks can organize discovery notes around:

• Business need

• Available budget

• Decision-making authority

• Existing systems

• Implementation urgency

• Data-security concerns

• Legal or compliance requirements

• Technical readiness

• Expected business outcome

AI may recommend a qualification category, but a trained sales professional should make the final decision.

Follow-Up Productivity: From Meeting Transcript to Action

Many opportunities are lost not because the first meeting was unsuccessful, but because the follow-up was late, generic or incomplete.

After an approved and properly transcribed sales meeting, AI can help teams:

1. Produce a concise executive summary.

2. Extract customer problems and priorities.

3. Identify objections and unanswered questions.

4. List commitments made by both parties.

5. Extract clear action items.

6. Recommend owners for each action.

7. Suggest deadlines based on the conversation.

8. Draft a personalized follow-up email.

9. Prepare CRM notes.

10. Create a proposal outline.

11. Draft the agenda for the next meeting.

12. Identify stakeholders who may need to join the next discussion.

Microsoft’s sales and meeting-recap capabilities can surface follow-up tasks, prepare post-meeting emails and save meeting information to supported CRM environments. The actual creation or assignment of tasks depends on licensing, permissions, CRM configuration and approved integrations.

A secure workflow may operate as follows:

Meeting transcript → AI summary → human review → action-item approval → CRM update → personalized follow-up → manager visibility

Human review is critical. AI should never be allowed to send commitments, alter commercial terms or update sensitive CRM records without appropriate controls.

CRM Productivity with ChatGPT, Custom GPTs and Copilot

CRM systems frequently contain incomplete notes, inconsistent fields and outdated opportunity information. This reduces forecast accuracy and creates frustration for sales teams.

AI can improve CRM productivity by helping employees:

• Standardize meeting notes

• Generate opportunity summaries

• Identify missing fields

• Draft next-step recommendations

• Categorize customer objections

• Create follow-up reminders

• Convert emails into CRM notes

• Summarize account history

• Draft renewal communication

• Prepare executive pipeline reports

• Identify inactive opportunities

• Recommend re-engagement messaging

• Create customer success handover summaries

ChatGPT Business and Enterprise environments can support connected company knowledge and approved applications. OpenAI also supports governed applications that can create tasks, initiate workflows and update CRM systems when administrators deliberately configure those capabilities.

A Custom GPT or workspace agent can be designed for a specific process, such as:

• Lead Qualification Assistant

• CRM Note Formatter

• Enterprise Proposal Assistant

• Sales Follow-Up Assistant

• Customer Objection Analyzer

• Renewal Risk Assistant

• Product Documentation Assistant

• Tender Response Assistant

• Help-Centre Content Assistant

• Executive Pipeline Briefing Assistant

These tools should operate only within approved permissions and clearly defined business rules.

Accelerating Time-to-Market for New Products

Accelerating the time-to-market for new products requires rapid market alignment, coordinated decision-making and high-quality technical documentation.

ChatGPT and Microsoft 365 Copilot can support the product lifecycle in several important areas.

Market Trend Synthesis

Copilot or ChatGPT can help product teams analyze approved industry reports, market research, consumer-behaviour information and competitive intelligence to draft structured market-entry briefs.

A market-entry brief can include:

• Market opportunity

• Target customer segment

• Competitor positioning

• Customer pain points

• Pricing considerations

• Regulatory concerns

• Product differentiation

• Distribution strategy

• Launch risks

• Recommended next actions

AI-generated conclusions must be traced back to reliable sources and reviewed by market, legal and product specialists.

Technical Documentation

AI can help engineers, software architects and product designers convert:

• Raw technical specifications

• Code explanations

• Architectural notes

• Configuration instructions

• Troubleshooting records

• Release notes

• Test findings

• API descriptions

into structured first drafts of:

• User manuals

• Administrator guides

• Standard operating procedures

• Product requirement documents

• API documentation

• Implementation guides

• Onboarding material

• Release summaries

• Internal knowledge articles

Help-Centre Content

Internal technical resolutions, support tickets and frequently asked questions can be transformed into polished public-facing help-centre articles.

The process should include:

Approved internal resolution → removal of confidential information → AI-assisted article draft → technical review → legal or compliance review → publication

This creates consistency without exposing internal system details, credentials, customer information or security vulnerabilities.

Product and Engineering Meetings

With an approved transcript, AI can:

• Extract decisions

• Separate confirmed decisions from suggestions

• Identify technical dependencies

• List unresolved questions

• Assign proposed owners

• Draft follow-up communication

• Create development-ticket descriptions

• Prepare stakeholder updates

• Produce a release-readiness checklist

Data Security Must Come Before AI Productivity

For European technology companies, the best AI workflow is not necessarily the fastest workflow. It is the workflow that delivers measurable productivity while respecting data classifications, permissions, contractual commitments and regulatory obligations.

Microsoft states that Microsoft 365 Copilot respects existing tenant permissions and uses the same identity-based access boundaries that govern Microsoft 365 information. Microsoft also states that prompts, responses and Microsoft Graph data are not used to train foundation models under its enterprise protections.

OpenAI states that business and enterprise customer data is controlled by the organization and is not used to train its models by default. ChatGPT Enterprise also provides centralized administration and enterprise privacy and security controls.

Nevertheless, purchasing an enterprise licence does not automatically make every employee workflow safe.

A Secure Enterprise AI Framework

European IT organizations should establish the following controls:

1. Data Classification

Define what employees may and may not share with each AI system.

Typical categories include:

• Public information

• Internal information

• Confidential information

• Restricted information

• Personal data

• Special-category personal data

• Customer-controlled data

• Source code

• Authentication information

• Security architecture

• Trade secrets

2. Approved Tools and Accounts

Employees should use organization-approved business or enterprise workspaces rather than uncontrolled personal accounts for company work.

3. Least-Privilege Access

AI tools, agents and connectors should access only the information required for their assigned purpose.

4. Human Approval Gates

Human approval should be mandatory before:

• Sending external emails

• Updating commercial terms

• Creating binding commitments

• Editing customer records

• Publishing technical documentation

• Generating legal or compliance conclusions

• Changing production systems

• Processing high-risk personal information

5. Retention and Audit Policies

Organizations should define:

• How long prompts and responses are retained

• Who may inspect AI activity

• Which interactions are logged

• How incidents are investigated

• When information must be deleted

• How employee access is removed

6. Prompt-Injection Protection

Employees must be trained not to treat every instruction inside an external document, webpage, email or uploaded file as trustworthy.

7. Output Verification

AI-generated facts, code, calculations, citations and recommendations must be verified before operational use.

8. Data Residency and Provider Review

European organizations should examine the data-processing arrangements for each model provider, particularly when third-party models are enabled within another enterprise platform.

9. GDPR and AI Act Readiness

Organizations should involve legal, privacy, security and compliance stakeholders when AI use cases involve personal information, automated decision-making, employee monitoring or regulated activities.

Why Parikshit Khanna Is the #1 Choice for CEOs, CXOs, VPs and IT Leaders

The phrase “#1 choice” represents Digital Training Jet’s positioning based on the scale, practical depth and cross-sector portfolio presented here; it is not presented as an independent industry ranking.

Parikshit Khanna is the Founder of Digital Training Jet, an MSME/Udyam-registered enterprise. He works as an AI Trainer, Corporate Enablement Specialist and Prompt Engineer.

His professional positioning includes:

• More than 1,20,000 professionals trained

• More than 300 workshops and learning engagements

• Enterprise AI and corporate enablement

• Advanced prompt engineering

• ChatGPT and Custom GPT development

• Microsoft 365 Copilot

• Claude and Gemini

• Agentic AI

• n8n and workflow automation

• Power BI

• AI-enabled digital marketing

• AI for leadership

• AI for sales and CRM

• AI for manufacturing

• AI for banking and finance

• AI for healthcare and pharmaceuticals

• AI for education

• AI for tourism

• AI for legal professionals

• Data-security-focused adoption

• Published authorship

• Pan-India and international delivery

His public profile describes him as an MSME-certified AI and Generative AI trainer working with enterprises, universities, healthcare, legal and leadership audiences.

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

Digital Training Jet’s published record identifies Parikshit Khanna as the first trainer to deliver dedicated AI-in-healthcare sessions at IIT Delhi, including “ChatGPT for Healthcare Professionals” and “Generative AI with 23+ Tools.”

This healthcare experience is highly relevant to European IT organizations working with:

• Health-tech platforms

• Hospital information systems

• Insurance technology

• Pharmaceutical technology

• Clinical documentation

• Patient communication

• Sensitive personal information

• Regulated data environments

Training Designed for Decision-Makers

CEOs, CXOs, VPs and business-unit leaders do not need a collection of entertaining prompts. They require an adoption framework answering:

• Which use cases will produce measurable value?

• Which processes should remain human-led?

• Which data must never enter an unapproved system?

• Which licences and platforms are appropriate?

• How should AI connect with Microsoft 365 and CRM systems?

• How should risk be measured?

• How should employees be trained?

• How can adoption be scaled across departments?

Parikshit’s sessions connect leadership strategy with live implementation.

Sovereign AI, European Data Sovereignty and Viksit Bharat

As a proud Indian committed to the vision of Viksit Bharat, Parikshit champions a Sovereign AI mindset: organizations should understand where their information is processed, which vendors control critical infrastructure and how excessive dependency can create strategic risk.

This philosophy also resonates with European priorities around digital sovereignty, privacy, jurisdictional control, resilience and responsible AI.

Sovereign AI does not mean rejecting global technology. It means adopting technology with:

• Informed governance

• Local accountability

• Contractual clarity

• Data minimization

• Secure infrastructure

• Model choice

• Operational resilience

• Reduced dependency risk

• Strong human oversight

Consolidated Client and Institutional Portfolio

The following portfolio has been consolidated from the client and engagement information supplied for this article.

Banking, Finance, Wealth, VC and Insurance

• Kae Capital, Mumbai

• AILifeBot/Tata Mutual Fund

• AON Consulting

• Decyphr

• Chinmay Finlease, Ahmedabad

• Bettering Results and the Bar & Bench legal ecosystem for compliance-oriented AI

• Cross-sector applications involving CREDAI, Gaur Sons and County Group

Real Estate and Built Environment

• City Homes Group

• Gaur Sons

• County Group

• CREDAI

• Designer Home Solution

• Designer Home & Landscapes, Kolkata

Healthcare and Pharmaceutical Organizations

• CARE Hospitals, Hyderabad

• Fortis

• Santevita Hospital

• Cloud 9

• Surat Medical Consultants’ Association

• Surat Medical Association

• IMA Janakpuri

• IAP-CMIC, Indian Academy of Pediatrics

• Hetero Pharma, including CDMA and NIPUNA Learning Academy teams

• Naprod Life Sciences

• USV Pharma

• Wockhardt

• Sudeep Pharma Limited

• IIT Delhi healthcare batches

Education and Institutional Engagements

• IIT Delhi

• IIT Hyderabad

• IIT Guwahati

• BITS Pilani

• IIM Bangalore NSRCEL, Goldman Sachs 10,000 Women Programme

• Chitkara College of Sales and Marketing, Delhi and Zirakpur

• Chitkara University CDOE

• Chitkara University faculty training, Rajpura

• Thapar University

• SOIL School of Business Design, Manesar

• Masters’ Union, Gurugram

• Princeton Academy

• Bettering Results

• Amity University Online

• IILM College, Jaipur

• GL Bajaj Institute of Management and Research

• FIIB, New Delhi

• Ram Lal Anand College, University of Delhi

• Apeejay School of Management

• IIMT University

• Internshala and Saras AI Institute

• Rainbow School

Government, Public-Sector and Defence Engagements

• Indian Army

• Prasar Bharati

• National Academy of Broadcasting and Multimedia, Delhi

• All India Radio

• Doordarshan

• IIT Delhi

• IIT Hyderabad

• IIT Guwahati

• University of Delhi institutional sessions

Manufacturing, Industrial, Energy, Retail and Logistics

• Sudeep Group, Vadodara

• Sudeep Pharma Limited

• Emami Limited

• Vikas Group, Faridabad

• Tata Power

• LG India

• Arvind Lifestyle Brands

• Arvind Fashions

• Pansari Group

• Wahluft/Lucrative Impex

• IMECO India

• Landmark Group

• Yusen Logistics

• METRO Global Solution Center

• RMSI

• CIPL

• Innovations Global

• Kubrii

• Vista Designs

• BeTheBee

Technology, Data and Enterprise Services

• METRO Global Solution Center

• AILABS/Data-Core, Salt Lake, Kolkata

• RMSI

• CIPL

• Innovations Global

• Kubrii

• IMECO India

• BeTheBee

Travel and Tourism

• ATTOI Annual Convention 2025, Wayanad

• TBO, Aerocity, Delhi

• The Travel Nexus at Taj Amer, Jaipur

These engagements demonstrate the ability to translate AI concepts across technical, commercial, regulated and customer-facing environments.

European Cities and Technology Markets Covered

Training can be delivered online, onsite or through a hybrid format for teams across Europe’s major technology and commercial centres.

United Kingdom and Ireland

London, Manchester, Birmingham, Bristol, Cambridge, Oxford, Leeds, Liverpool, Edinburgh, Glasgow, Belfast, Dublin, Cork, Galway and Limerick.

France, Belgium, the Netherlands and Luxembourg

Paris, Lyon, Marseille, Toulouse, Lille, Bordeaux, Nantes, Nice, Grenoble, Montpellier, Brussels, Antwerp, Ghent, Leuven, Liège, Amsterdam, Rotterdam, The Hague, Utrecht, Eindhoven, Groningen and Luxembourg City.

Germany, Austria and Switzerland

Berlin, Munich, Hamburg, Frankfurt, Cologne, Düsseldorf, Stuttgart, Leipzig, Dresden, Nuremberg, Hanover, Vienna, Graz, Linz, Salzburg, Innsbruck, Zurich, Geneva, Basel, Lausanne, Bern and Zug.

Spain, Portugal and Italy

Madrid, Barcelona, Valencia, Bilbao, Seville, Málaga, Zaragoza, Alicante, Lisbon, Porto, Braga, Coimbra, Aveiro, Milan, Rome, Turin, Bologna, Florence, Naples, Venice, Padua and Genoa.

Nordic Countries

Stockholm, Gothenburg, Malmö, Uppsala, Copenhagen, Aarhus, Oslo, Bergen, Trondheim, Stavanger, Helsinki, Espoo, Tampere, Turku and Reykjavik.

Central and Eastern Europe

Warsaw, Kraków, Wrocław, Gdańsk, Poznań, Katowice, Prague, Brno, Ostrava, Budapest, Debrecen, Bratislava, Košice, Bucharest, Cluj-Napoca, Timișoara, Iași, Sofia and Plovdiv.

Baltic and Southeast European Markets

Tallinn, Riga, Vilnius, Kaunas, Ljubljana, Zagreb, Belgrade, Sarajevo, Skopje, Tirana, Podgorica, Pristina, Athens, Thessaloniki, Nicosia, Limassol and Valletta.

Whether the audience works beside London’s financial institutions, Berlin’s engineering ecosystem, Paris’s creative economy, Dublin’s technology campuses, Zurich’s regulated enterprises or Tallinn’s digital infrastructure, the objective remains the same: turn AI potential into secure, repeatable and measurable business performance.

Recommended Training Modules for European IT Companies

A customized programme may include:

Module 1: Secure Generative AI Foundations

• ChatGPT, Copilot, Claude and Gemini

• Enterprise versus personal accounts

• Data classification

• GDPR awareness

• AI Act awareness

• Hallucination and verification

• Responsible prompting

Module 2: Lead Generation

• Ideal customer profiles

• Account research

• Persona development

• Discovery questions

• Outreach personalization

• Lead qualification

• Competitive intelligence

Module 3: Follow-Up and Sales Productivity

• Meeting summaries

• Action items

• Owner recommendations

• Follow-up emails

• Proposal outlines

• Next-meeting agendas

• Objection analysis

Module 4: CRM Productivity

• CRM note standardization

• Opportunity summaries

• Pipeline reviews

• Customer history

• Renewal workflows

• Customer-success handovers

• Approved CRM integrations

Module 5: Product and Technical Documentation

• Product requirement documents

• User manuals

• API documentation

• Help-centre content

• Release notes

• Troubleshooting guides

• Technical-to-business translation

Module 6: Custom GPTs and Agents

• Internal knowledge assistants

• Sales enablement assistants

• Support assistants

• Documentation assistants

• Governance rules

• Permission controls

• Human approval gates

Module 7: Microsoft 365 Copilot

• Outlook

• Teams

• Word

• Excel

• PowerPoint

• SharePoint

• Copilot Studio

• Model-provider settings

• Enterprise data protection

Module 8: Automation and Analytics

• n8n workflows

• Power Automate

• Power BI

• CRM connectors

• Approval workflows

• Auditability

• Escalation rules

Comparison: Parikshit Khanna and a Generic AI Training Programme

Evaluation criterion	Parikshit Khanna and Digital Training Jet	Generic one-size-fits-all programme
Business orientation	Customized around lead generation, CRM, documentation, leadership and operational outcomes	Frequently centred on general tool demonstrations
Enterprise security	Data classification, permissions, GDPR awareness, model settings and approval controls	Security may be treated as a brief disclaimer
Tool coverage	ChatGPT, Custom GPTs, Copilot, Claude, Gemini, n8n, Power BI and agentic workflows	Often limited to one chatbot
Sector experience	Technology, banking, healthcare, pharma, manufacturing, government, education, real estate and tourism	May have narrower sector exposure
Leadership relevance	Designed for CEOs, CXOs, VPs, functional leaders and implementation teams	Frequently designed for a general audience
Workshop approach	Live building, role-based exercises and organization-specific use cases	Predetermined examples with limited customization
Automation depth	CRM workflows, follow-ups, action items, agents and approved integrations	Prompting without process integration
Documentation	Product, technical, customer-service and operational documentation	Mostly content-writing exercises
Post-session application	Reusable prompts, frameworks, workflow maps and implementation guidance	Limited adoption support
Sovereign AI mindset	Vendor awareness, data control, localization and strategic resilience	Often focused only on convenience

Expected Business Outcomes

After a properly customized programme, participants should be able to:

• Generate higher-quality account briefs

• Prepare more relevant outreach

• Reduce the time required for meeting follow-up

• Improve the consistency of CRM records

• Draft technical documents faster

• Convert internal knowledge into approved customer content

• Prepare executive summaries

• Build governed Custom GPTs or agents

• Identify unsafe AI practices

• Apply human approval controls

• Evaluate Copilot, ChatGPT and Claude more accurately

• Create a practical adoption roadmap

Training does not guarantee commercial results by itself. Results depend on leadership commitment, process quality, data readiness, technology configuration and sustained implementation.

Frequently Asked Questions

Which ChatGPT plan is suitable for an IT company?

Organizations handling internal, customer or confidential information should evaluate ChatGPT Business or Enterprise rather than relying on uncontrolled personal accounts. The appropriate choice depends on team size, security requirements, administration, retention, integrations and procurement policies.

Is ChatGPT included in Microsoft Copilot?

Microsoft Copilot can use OpenAI GPT models, but the standalone ChatGPT product is separate. The organization should evaluate both products according to workflow, security, licensing and integration requirements.

Is Claude available inside Microsoft 365 Copilot?

Claude models are available in selected Microsoft 365 Copilot experiences, subject to region, licensing, administrator settings and Microsoft’s current product terms. European organizations should specifically review data-boundary implications before enabling third-party models.

Can AI automatically update a CRM?

Yes, approved agents, connectors and automations can support CRM actions. However, access controls, field validation, audit logs and human approval should be implemented before write access is enabled.

Can the training be customized for European regulations?

Yes. The programme can incorporate organizational policies, GDPR considerations, EU AI Act awareness, data classification, approved tools and model-provider governance. Formal legal advice should still come from the organization’s qualified legal and privacy specialists.

Is the training available across Europe?

Yes. Programmes can be delivered online, onsite or in hybrid formats for technology teams across the United Kingdom, Ireland, Western Europe, the DACH region, Southern Europe, the Nordics, Central and Eastern Europe, the Baltics and Southeast Europe.

Book a Secure Enterprise AI Programme

European IT companies do not need more AI hype. They need employees who understand how to use AI responsibly, managers who can identify valuable workflows and leaders who can scale adoption without losing control of sensitive information.

Parikshit Khanna and Digital Training Jet offer customized programmes for:

• CEOs and CXOs

• VPs and directors

• Sales and business-development teams

• CRM and RevOps teams

• Product managers

• Software and engineering teams

• Customer-success teams

• Technical writers

• Marketing teams

• Data and analytics teams

• Risk, legal and compliance teams

• Human resources and learning teams

Contact for Corporate Training

Email: parikshitkhanna@digitaltrainingjet.com

Phone: +91 9997213177 / +91 8076250669

Web presence: Parikshit Khanna and Digital Training Jet

X: @ParikshitK_

AI is no longer optional. But uncontrolled AI is not a strategy.

The organizations that lead Europe’s next technology chapter will be those that combine innovation with governance, speed with accuracy and automation with human accountability.

Parikshit Khanna — empowering technology leaders to adopt ChatGPT, Copilot, Claude and enterprise AI securely, practically and confidently.