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Objective
CFA Institute is launching the Member AI Hub. One of the founding pillars is member-to-member content: short articles written by members, for members, on what AI is actually changing in their work.
This call is for that content. We are asking members to share, in their own words, what AI is changing in their practice — the prompts that earned their keep, the workflow that broke, the question your team had to answer before the model went live.
Submissions are reviewed against the CFA Institute Code of Ethics and Standards of Professional Conduct and routed through editorial, peer review, brand, risk, and legal before publishing.
Why this matters now
Members tell us they want practical, peer-tested guidance on AI and we want real practitioner pieces in the queue when it goes live.
What we're asking for
One 600 to 800 word article that takes one specific thing you have worked on with AI and tells the truth about it: what you tried, what changed, what surprised you, what you would do differently.
Submission format
Each submission has three parts.
- Article (600 to 800 words). A focused piece on one practical AI topic. What you tried, what happened, what you would tell a peer.
- AI Tools and Process Used (required second section, 75 to 150 words). A short, plain-language disclosure: which AI tools (if any) you used while writing, what they did (drafting, editing, ideation, summarization), and what you reviewed yourself.
- Author bio (50 words). Your role, organization (if you can name it), CFA Institute member status, and one line on why this topic.
Topics we want to cover
Choose one of the below or pitch us something we haven't mentioned. The eight buckets below come from member interviews conducted by our membership team.
- Practical AI on the Job. Real workflows in research, portfolio, trading, and risk, with case examples from real firms. Tell colleagues what’s actually working in roles like theirs.
- AI and Your Career. How AI is changing hiring, resumes, candidate screening, and the skills employers want next. Help peers stay marketable as the bar moves.
- AI Foundations for Finance. What AI actually is, how large language models work and break, plus the ethics and regulation around them. Give peers a credible foundation for asking sharper questions.
- Ethics in an AI-driven investment world. Responsible use of AI in finance, managing bias,hallucination, and misinformation, transparencyand explainability in AI outputs.
- AI Tools and Data Skills. Hands-on work with Python, Bloomberg, FactSet, and AI tools for extraction, analysis, and reporting. Help peers build the technical fluency that turns ideas into shipped work.
- AI in Markets and New Products. AI in ETFs, derivatives, alt data, private markets, credit, and emerging asset classes. Help peers spot product and strategy risks before they show up in performance.
- AI for Daily Workflow. Automating research, reporting, summarization, and market monitoring. Help colleagues buy back hours every week for the work only they can do.
- AI and Human Judgment. When to trust AI, when to push back, and how to combine model output with practitioner expertise. Help peers stay in the driver’s seat with AI in the loop.
Pitch ideas by career stage
If you are not sure what to write, start with where you are in your career. We use the same Early / Mid / Senior segmentation as the Career Library.
Early career
- How I built my first AI workflow without writing code.
- Five prompts every analyst should keep in their back pocket.
- The first AI tool I tried, and what I would tell my past self.
- What I wish someone had explained before my first model output.
- Reading a model card: a short field guide for investment teams.
Mid career
- What an LLM caught in a 10-K that I missed.
- Backtesting a sentiment signal: where the alpha actually was.
- When AI helps with rebalancing — and when it adds drift.
- Three model-risk failures we caught in validation.
- Personalizing client letters without losing the human voice.
Senior career
- Build vs. buy: the real cost of running our own model.
- Disclosure that a client actually reads: rewriting our AI policy.
- Auditing a model for fairness: what we found, what we changed.
- Reskilling a 40-person research team: a candid year-one report.
- What 'AI-fluent investment professional' means on our team.
Topics to avoid
- Specific buy/sell recommendations or current-market calls.
- Promotional content for vendors, products, or your firm.
- Confidential, client-identifying, or non-public material.
- Politically charged commentary unrelated to investment practice.
- Undisclosed AI generation. Anything written or substantively edited by an AI tool must be disclosed in the AI Tools and Process Used section.
Why your perspective matters
Members do not want another vendor explainer. They want to know what worked for someone whose job looks like theirs. When you publish on the Member AI Hub, you give your peers a real reference point and give CFA Institute the practitioner signal that informs research and policy.
What's in it for you
- Reach the global CFA Institute member community on the AI Hub.
- A byline on a peer-reviewed piece in CFA Institute's voice and channels.
- Invitations to speak in expert sessions tied to your topic.
- Recognition as a founding contributor to the Member AI Hub.