Training course · Perplexity · Media & Journalism

Perplexity for Media and Journalism

AI-powered research with Perplexity: cited answers, source control, Spaces, Deep Research and systematic fact-checking.

Duration
1 day (7 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

This course connects Perplexity with the everyday processes of Media & Journalism. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.

Perplexity combines language models with live web search and delivers answers backed by numbered citations. That makes it particularly suited to work where currency and traceability matter: market and competitor monitoring, research into regulation and standards, supplier and partner due diligence, or preparing decision papers. In this practical day you learn to phrase research questions precisely, steer the choice of sources deliberately and use follow-up questions to turn an initial answer into a robust research result.

You work with Spaces, where you group research on a topic, add your own files and set instructions for the team. With Deep Research you produce extensive reports that evaluate many sources and bring them together in a structured way. Quality is a key focus: you learn to assess sources, cross-check claims and recognise typical failure patterns such as outdated or misattributed information. We also address data protection and licensing questions for business use. You leave with a reusable research process tailored to your own function.

Newsrooms, publishers, broadcasters and content teams are caught between economic pressure and the demands of quality journalism. Generative AI is fundamentally changing research, production and distribution. It helps reporters work through documents and datasets faster, transcribe and summarise interviews, develop headline and teaser variants, adapt stories for different channels and make archives searchable. AI agents can sort wire copy or handle monitoring tasks. At the same time, AI raises core questions: how do you safeguard accuracy, how do you make AI use transparent to your audience and how do you respect copyright? Media professionals therefore need competence in both productive use and critical verification.

The course is delivered live – either online in a virtual classroom or on-site in our training rooms in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run it exclusively for your team.

Who is this course for?

  • Reporters and editors in print, online and broadcast
  • News desk chiefs and section editors
  • Social media and audience teams
  • Freelance journalists
  • Content and corporate publishing teams

Typical challenges we address

  • Intense time pressure alongside a growing number of channels and formats
  • Large volumes of documents, data and wire material
  • Safeguarding accuracy and credibility
  • Unresolved questions about copyright and labelling of AI content

What you will be able to do

  • You phrase precise research questions and steer the choice of sources deliberately.
  • You assess sources by origin, currency and reliability and trace claims back to the original.
  • You organise research in Spaces and combine web sources with your own documents.
  • You use Deep Research to produce structured reports and decision support.
  • Use AI for research, transcription and production efficiently and faithfully to sources.
  • Check AI output systematically for accuracy and avoid typical pitfalls.
  • Apply rules on copyright, labelling and press ethics confidently when using AI.

Course outline

Module 1 Foundations of AI-powered research
  • How it works: language model, live web search and citations
  • How it differs from a classic search engine and a general chat assistant
  • Framing research questions precisely: time frame, region, source type
  • Follow-ups and drilling down instead of one-off queries
Module 2 Steering and assessing sources
  • Narrowing sources: web, academic literature, your own files
  • Targeting primary sources, official websites and specialist publications
  • Assessing source quality: origin, currency, vested interests
  • Tracing quotes and figures back to the original source
Module 3 Spaces and teamwork
  • Setting up Spaces for topics, projects or client requests
  • Uploading your own documents and combining them with web sources
  • Storing instructions for consistent output formats
  • Sharing research and turning it into pages or reports
Module 4 Deep Research and structured reports
  • Tackling broad questions with Deep Research
  • Producing market overviews, competitor comparisons and topic briefs
  • Turning results into tables, side-by-side comparisons and executive summaries
  • Recognising the limits of in-depth research and refining results
Module 5 Fact-checking, data protection and workflow
  • Systematic fact-checking: counter-research and spotting contradictions
  • Typical failure patterns: outdated, misattributed or fabricated details
  • Data protection, enterprise licences and handling confidential queries
  • A reusable research process and source documentation
Module 6 Practice lab: Media & Journalism
  • Document research
  • Transcribing and analysing interviews
  • Headlines and teasers
  • Adapting formats
  • Unlocking the archive
  • Supporting fact-checking
Module 7 Data protection, quality & transfer to daily work
  • Press codes and journalistic due diligence apply unchanged: AI output must be verified and AI use made transparent to the audience in line with in-house guidelines. Copyright and related rights in source material and generated content must be respected, and source protection rules out entering confidential source information into unapproved tools.
  • Ground rules for safe AI use in your team
  • Checking results: facts, sources, tests and the four-eyes principle
  • Personal action plan for the next 30 days
  • Open questions, outlook and resources for further learning

Practical scenarios from your field

Document research

Lengthy reports, court rulings, budgets or leaked datasets are searched and summarised with AI and checked for relevant passages – every statement is then verified against the source.

Transcribing and analysing interviews

Audio and video interviews are transcribed, key statements and quotes are highlighted and sorted by topic, so stories can be written faster and quotes attributed precisely.

Headlines and teasers

For a finished story, AI generates variants for headlines, standfirsts, social posts and push alerts that match the brand's tone and from which the editors choose.

Adapting formats

An article is turned into newsletter summaries, explainers, podcast scripts or easy-read versions without changing what it says. Editors check every version for accuracy and house style before publication.

Unlocking the archive

Archive material is tagged, summarised and made searchable so that background, timelines and earlier coverage can be retrieved quickly. Dossiers on people, places and topics stay up to date with little effort.

Supporting fact-checking

AI helps identify checkable claims in texts, formulate verification questions and point out contradictions; the verification itself is done with primary sources. Due diligence becomes more systematic.

Prerequisites

Experience with online research in a professional context; no prior AI knowledge is required. Professional experience in journalism or editorial work; no technical background required.

Technical requirements

A laptop with an up-to-date browser and a Perplexity account; we recommend Pro or Enterprise access to use Spaces with files and Deep Research in full.

Data protection & compliance

Press codes and journalistic due diligence apply unchanged: AI output must be verified and AI use made transparent to the audience in line with in-house guidelines. Copyright and related rights in source material and generated content must be respected, and source protection rules out entering confidential source information into unapproved tools.

Suggested dates

All dates are suggestions – your preferred date is always possible.

  • Tue, 24 November 2026 Online Request
  • Thu, 3 December 2026 Kaiserslautern Request
  • Wed, 9 December 2026 Online Request
  • Fri, 8 January 2027 Online Request
  • Thu, 21 January 2027 Augsburg Request
  • Wed, 27 January 2027 Online Request

Frequently asked questions

How does Perplexity differ from ChatGPT or a search engine?

A search engine returns a list of links, and a general chat assistant often answers from its training data. Perplexity searches the web at the moment you ask, summarises what it finds and backs each statement with citations. That makes it particularly well suited to current, verifiable research – although you still need to assess the sources yourself.

Can I rely on Perplexity's citations?

Citations make verification much easier, but they do not replace it. Occasionally a statement is attributed to a source that does not say quite that, or an outdated page is used. In the course you learn a lean fact-checking routine that lets you quickly verify critical statements against the original source.

Is Perplexity suitable for confidential research within a company?

Enterprise plans offer additional commitments on data use and administration. Even so, you should not put trade secrets or personal data into queries unless your internal policy explicitly allows it. We discuss how to phrase queries so that sensitive details stay protected while the research remains useful.

Does AI-generated content need to be labelled?

That is determined by legislation, voluntary commitments and your organisation's guidelines. The EU AI Act sets transparency obligations for certain AI-generated content, and many newsrooms go further with their own policies. In the course we discuss when labelling is required and how to document editorial responsibility.

Can I use AI for fact-checking?

AI helps identify checkable claims and plan verification steps, but it is not a reliable source in itself. Language models can state false facts plausibly. Verification always relies on primary sources, documents and conversations. The course demonstrates a workflow that uses AI as an assistant without compromising rigour.

How much does “Perplexity for Media and Journalism” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 1 training day(s) with a live trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. Our suggested dates are just a guide. In the request form you can always describe your preferred date or period in free text – we check availability and confirm within one working day.

Is the course online or on-site?

Both are possible: live online in a virtual classroom or on-site in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart or Kaiserslautern. We can also run the course exclusively for your team.

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