Why are agencies hiring AI assistants as junior analysts?
Agencies are hiring AI assistants as junior analysts because these agents act like tireless junior team members who handle data gathering, basic analysis, and reporting tasks at a fraction of the cost, allowing human analysts to focus on strategic work.
The junior analyst role is being redefined by AI
Junior analysts are typically tasked with researching financial trends, valuations, and economic data, but in practice the role involves a lot of tedious and repetitive tasks like updating charts in pitch decks and company valuation comparison tables. What used to take a junior analyst 4 hours a day now takes an AI agent just 20 minutes.
Big firms are reportedly considering pulling back hiring as much as two-thirds as Wall Street relies more on AI, including at renowned firms like Goldman Sachs and Morgan Stanley. Many of the research and basic analysis tasks traditionally performed by junior consultants and analysts could likely be replaced by AI in the future.
Why agencies are making the shift now
AI begins to remove the grunt work typically given to entry level employees, with highly rules-based but tedious work like QA of data, real-time flowchart updates, media tagging and trafficking done just as effectively by machines.
Research assistants designed to automate the grunt work that comes with survey reporting can 50-500x manual reporting workflows and eliminate the cold start that slows down so many researchers. AI agents are data vacuum cleaners on steroids, sucking up information from countless sources and organizing it faster than you can say market segmentation.
Cost and efficiency advantages are driving adoption
One of the key reasons why AI may disrupt entry-level financial services positions is its potential to automate the information processing that comprises a large portion of their job description. What once took weeks now happens in real-time with lower resource investment and reduced costs.
Traditional market research analysis can be time-consuming, involving manual data cleaning, coding, and statistical analysis, but AI agents automate these tasks, processing large volumes of data in minutes and delivering key findings almost instantly.
AI agents handle multiple analyst functions autonomously
Companies are designing agents that perform a select portion of the market research process, such as data collection, segmentation, and simulations. AI agents can crunch through terabytes of data in minutes, constantly scanning social media, news outlets, and online forums, giving real-time insights into market trends and consumer sentiment.
These AI agents are beginning to act like junior analysts as they are fast, tireless, and always watching the data for changes, making agentic analytics active, smart, and always on.
The strategic implications for agencies
AI will fundamentally redefine the role rather than necessarily take all entry-level jobs away. AI is reshaping jobs, pushing entry-level roles to evolve beyond their traditional contours and emphasizing skills that AI cannot easily replicate.
While AI agents pose a threat to entry-level employees, they also create opportunities, as those who can learn to work alongside AI agents become more valuable than someone who just does basic tasks. AI agents are turning market research analysts into strategic powerhouses, freeing up mental bandwidth for creative problem-solving and big-picture thinking.
How to build your Lemonade for research automation
-
Create a New Lemonade – Set up a dedicated assistant for market research and data analysis
-
Choose a Model – Select a model optimized for data processing and analytical reasoning
-
Make Clear Instructions – Define research methodologies, data sources, analysis frameworks, and reporting formats
-
Upload your custom Knowledge – Feed in research templates, industry reports, analytical frameworks, and past project examples
-
Run Lemonade and Test – Process sample datasets and refine based on output quality and analytical depth
Pro Tips
The beauty of AI agents in market research is that they augment human capabilities rather than replace them, freeing up human researchers to focus on strategy and creative problem-solving while handling the heavy lifting of data processing and initial analysis.
Many junior analysts will be freed from routine tasks and move into roles requiring deeper human insight, while AI-literate consultants who can operate and validate AI agents will see elevated profiles.
The demand for human capabilities such as critical thinking, stakeholder communication, creativity, and data storytelling will intensify as AI handles mechanical work, with adaptability and continuous learning no longer optional but essential survival skills.
A knowledge transfer gap develops when AI agents replace rote tasks, as there is benefit to learning nuts and bolts tasks when managing people doing them to help troubleshoot and work through issues in real-time, drawing on executional experience.
To stay updated with us, please follow our Facebook, Instagram, LinkedIn, Threads, TikTok, X, and YouTube pages.
