Data & AI Warsaw Tech Summit 2026 - Call For Presentations! Survey

1.Name of the speaker
(if there is more than one speaker proposed please add number (like 1.) for each name and then accordingly for other fields related to the speaker, like a bio).(Required.)

2.Speaker bio

3.Speaker experience
(provide any information about your previous speaking experience at public conferences, meetups and/or workshops. Links to YouTube videos or your conference talks are welcomed)

4.Speaker e-mail contact address(Required.)

5.Speaker phone number

6.Speaker formal position and company name (major one if there are a few)

7.Title of the presentation(Required.)

8.Description of the presentation
(detailed description of your presentation to help the Program Committee to better understand its aim and scope). This is for the eyes of Selection Committee only, so could be INFORMAL.(Required.)

9.Summary of the presentation [SHORT BUT FORMAL! - for the purpose of publishing presentation description in the conference agenda]
(we ask for 3-5 bullets with presentation outline - something that we might use later on the conference website in Agenda pane in case when your presentation is chosen - so this is important point!). This text might be published on the Internet - so PLEASE MAKE THIS THE WAY WE HAVE ASKED FOR!

10.Which conference track will be best fit for this presentation?
If you are not sure about this, you could mark max 2 suitable tracks.(Required.)

Data Architecture, Modernization & Engineering
Build the foundations for modern data-driven organizations. Learn how to design scalable data platforms, plan migrations/modernizations, optimize pipelines, and enable seamless access to trusted data. This domain focuses on topics like automated data processing, DataOps, data lakehouses, lineage tracking, and transformation frameworks like dbt , Spark or DuckDB. Talks explore real-world strategies for streamlining pipeline operations, solving data integrity issues, and optimizing engineering workflows. Ideal for engineers and architects working to modernize and monitor data infrastructures.

Operational Data, Streaming & Real-time analytics
Data in motion drives decisions. This track explores real-time and streaming architectures for processing operational data at scale. Learn how organizations are enabling real-time analytics, customer-facing dashboards, and operational intelligence systems. Talks highlight streaming technologies, event-driven design, and best practices for delivering insights when they matter most.

Generative AI, LLMs & Agents
Explore the power of generative models and intelligent agents. From LLM applications to agents & agentic frameworks, see how these technologies are transforming industries and reshaping the way humans and machines collaborate. Sessions blend technical depth with applied use cases across domains.

Using AI for Data
AI is not just the output — it's part of the process. This track focuses on using AI to enhance data engineering, governance, and analytics workflows. Learn how AI-driven tools can extract structured data from unstructured sources, automate data processing, perform intelligent data quality checks, streamline governance workflows, and enable natural language interfaces for complex business questions. Explore practical applications where AI becomes an embedded processing layer in your data value chain.

ML/AI & Data Science: from Research to Production
The complete machine learning lifecycle. Sessions cover traditional ML algorithms, statistical modeling, experimentation, and modern MLOps practices. Learn how organizations develop, deploy, monitor, and scale ML systems in production environments. Topics include model development workflows, deployment strategies, A/B testing, reproducibility, and bridging the gap between data science research and reliable operational systems.

Platform Engineering
Self-service cloud infrastructure for data and AI teams. Explore how platform engineering enables data and analytics engineers to deploy, scale, and secure their workloads through automated, governed infrastructure. Topics include container orchestration, infrastructure automation, developer portals for data teams, IAM and access controls, security frameworks for AI systems, and multi-cloud strategies that balance autonomy with governance.

AI Native Data Engineering
Accelerate data and AI development with AI-powered engineering tools. This track explores how AI copilots and coding assistants are transforming the Analytics Development Lifecycle (ADLC) - from data pipeline development to ML model deployment to platform engineering. Learn about tools like Claude Code, Cursor, and GitHub Copilot for analytics engineering, AI agents in notebooks, AI-powered SQL generation, and spec-driven frameworks for streamlined pipelines. Sessions cover real-world integrations, productivity gains across the ADLC, and best practices for AI-assisted engineering.

Analytics, BI & Visualisation
urn data into insights that matter. This track showcases modern BI platforms, data storytelling techniques, and advanced visualisation approaches for impactful decision-making. Expect practical guidance on building dashboards, communicating with stakeholders, and driving adoption of analytics tools.

Data & AI Governance & Quality
Building trust through governance and quality. This track focuses on the business frameworks and practices that ensure data and AI systems are reliable, compliant, and trustworthy. Sessions cover data governance strategies, quality assurance processes, regulatory compliance, bias detection and mitigation, and organizational practices for responsible AI. Learn how to establish governance frameworks, implement quality controls, and build stakeholder confidence in your data and AI initiatives.

Data Privacy, Security & Compliance
Navigating privacy and security in regulated environments. This track addresses the business and architectural challenges of data privacy, security, and regulatory compliance. Sessions cover regulatory frameworks (GDPR, CCPA, sector-specific regulations), risk management strategies, compliant data architectures, cross-border data governance, and balancing innovation with regulatory requirements. Ideal for business leaders, architects, and teams operating in highly regulated industries like healthcare, finance, and government.

Data and AI Strategy
Align data and AI initiatives with business goals. Learn how to drive innovation, measure impact, and build sustainable strategies that scale across organizations. Sessions highlight leadership perspectives, change management, and success stories from enterprises putting strategy into action.

Data & AI Across Industries (alternative: Domain & Vertical Enablers)
See data and AI in action across industries. Real-world stories from diverse sectors including healthcare, finance, manufacturing, retail, public sector, and beyond. This track highlights lessons learned, cross-industry patterns, and the unique challenges of applying data and AI in regulated or specialized domains.

11.Presentation format
We have few formats available in the conference agenda - which of the below might be suitable for your subject proposal? You can choose multiple options - all of the are equally important.(Required.)

Presentation shorter - 20 minutes onsite (+q&a)

Presentation longer - 30 minutes onsite (+q&a)

Roundtable discussion session onsite (you would be a moderator of the group discussion)

Workshop online (for 60 or 90 minutes)

12.Audience information
(who is the presentation for - in terms of skills, professional interest, job function?)(Required.)

13.How would you rank your presentation? Where 1- very technical, 5 - mostly business related(Required.)

For geeks only, real core

1 star

Tough but understandable

2 stars

Good mix beetween hard tech and practical application

3 stars

Business focus, yet still technical

4 stars

Even my CEO might understand it

5 stars

14.Please give us up to 5 keywords/#hashtags describing your presentation. This might be published in conference agenda.

15.Additional information
(any other information that supports your submission and profile)

16.We aim for hybrid event, so both online and onsite presentation is feasible. Would you be interested to come in person do Warsaw, Poland?

Yes

No

I have to think about it/TBD later

17.If you have answered YES to last question: organizers do not provide speaker's fee, however in a case, where it would be really necessary, we might cover the cost of accomodation and travel

No, I do not need this kind of support from the organizers

Yes, I do need the cost of accomodation in Warsaw to be covered by the organizers

Yes, I do need the cost of travel to be covered by the organizers

Not sure, to be decided later

18.Where did you get the information about this CFP?

Other (please specify)

19.Do you have any other comments, questions, or concerns?

20.Has this presentation been presented at any conference prior to Data & AI Warsaw Tech Summit?(Required.)

No

Yes

21.And the last thing - if you may upload your photo (for speakers bio purposes)

No file chosen

22.Consent to collect personal data(Required.)

I consent to the placement of my personal data in a database and their use for the purposes of organizing the process of collecting CFP applications at the Data & AI Warsaw Tech Summit 2026 conference. The administrator is Evention sp. z o.o., ul. Racławicka 93, 02-634 Warszawa, +48 tel. (22) 535-30-33, zgody@evention.pl, REGON: 146871262, NIP: 5252564839 entered under the KRS number: 0000483800 in the Rejestru Przedsiębiorców przez Sąd Rejonowy dla m.st. Warszawy, XIII Wydział Gospodarczy Krajowego Rejestru Sądowego. The data is stored in the cloud environment of the SurveyMonkey online survey service, in accordance with the service policy - https://www.surveymonkey.com/mp/gdpr/ - and in accordance with the Data & AI Warsaw Tech Summit 2026 Conference Regulations. The data will not be transferred to anyone and can be deleted at any time upon request.

Please do click on the Submit button below - to feed the CFP database!