Zuckerberg to Replace Mid-Level Engineers by 2025

AI | Jan 14, 2025

Image: Freepik/DC Studio

Mark Zuckerberg Announced the Ability to Automate Mid-level Engineering Roles at Meta by 2025

Job automation has been going on for decades but Mark Zuckerberg just doubled down on an episode of Joe Rogan's Experience podcast when he announced plans to automate mid-level engineering roles at Meta some time in 2025.  Of course if Meta is doing this then so will all the other companies working on AI will too.  That is, AI systems will autonomously soon write code that could become operational, they would effectively update and maintain it too.

🚨 Mark Zuckerberg on the Joe Rogan podcast

in 2025, AI systems at Meta and other companies will be capable of writing code like mid-level engineers.

at first, it's costly, but the systems will become more efficient as time passes.

eventually, AI engineers will build most of… pic.twitter.com/iJtJqgXm19

— Haider. (@slow_developer) January 10, 2025

The dominoes are starting to fall, raising near term practical questions about the future of work and its impact on human employees.  Some countries like the UK and Canada with declining growth and aging populations are looking to AI to increase productivity.  Companies are starting to launch their own AI agents like Salesforce's Agentforce to innovate and boost growth/productivity while reducing operational costs.  Or Moody's who have integrated AI as 'digital colleagues' through a multi-agent system whose AI agents automate processes such as financial risk analysis, PESTLE assessments, and credit evaluations saving them a ton of time while freeing up human decision-makers to focus on strategic initiatives.

Some Financial Jobs at Risk from AI

AI's ability to replace or completely transform traditional jobs goes far beyond coding.  In the financial sector, many roles rely on repetitive, data-driven tasks which are of course at high risk.

See:  AI, Funding Shifts and Regulatory Hurdles in Fintech 2024

We asked AI to help predict and rank the financial jobs that it thinks AI will replace, when it will replace it and it's impact on an 'evolved human role' in the broader task.  The results are in the table below.

Preparing for the new Digital Workforce and Human Collaboration

As artificial intelligence because more and more integrated into core business operations, fintech companies need to rethink strategies and prepare for a blends AI with human capabilities.  Success will depend on setting clear objectives, embedding ethical practices, and fostering collaboration to create what can be called a 'bionic fintech' era, an integrated partnership with human creativity and AI's precision and speed.

1. Define Your AI Priorities (where AI delivers the biggest win)

Fintechs must evaluate their business models and identify the processes and services that will benefit the most from AI integration. For example, payment processors can use AI to improve fraud detection and optimize transaction speeds while wealth tech platforms could use AI to deliver personalized financial advice and enhance customer service.

See:  How Real-Time Agentic AI Will Boost Fintechs

By clearly defining these priorities, companies can ensure their AI investments are aligned with meaningful goals and provide measurable value over time.

2. Start Small but Dream Big!  Scale AI Without the Risk

Implementing AI doesn't have to be a huge gamble.  Start by launching a strategic yet small pilot project in a high priority area such as compliance automation or risk assessment where potential solutions can be tested and refined before wider deployment.  Platforms such as AWS AI/ML Solutions or Google Cloud AI can provide the tools needed to experiment.  Then expand AI capabilities as new processes prove successful, reducing the risk of large-scale failures.

3. Commit to Responsible AI (given that AI needs a moral compass)

A trustworthy AI system can only be built on an ethical foundation.  Companies must prioritize transparency, accountability, and compliance with regulations to build AI systems that are trusted with confidence.  Frameworks like the UK's Data Ethics Framework can serve as a guide to help fintechs avoid bias/risks and develop AI systems that are both effective and socially responsible.

4. Redefine Human Superpowers and Prepare Team for Success

Make sure people understand that while AI is great at handling repetitive, data  heavy tasks, humans are necessary for creativity, empathy, and ethical oversight.  As AI eventually takes over routine tasks, humans can manage these systems, tweak strategies, and work on complicated challenges that machines can't resolve.  Human ingenuity is sill at the top of the food chain (for now anyways)!

See:  Musk Says Human Data for AI Training is Depleted

Companies must provide the necessary up-skilling and training programs on AI, data literacy, and problem-solving to teach employees how to effectively work with AI systems and generate high value outputs.  Given the right tools and training, employees should be able to trouble shoot exceptions and better understand nuanced findings. Creating an environment that encourages learning and adaptability ensures employees remain relevant and capable in this changing landscape.

5. Integrate AI into Workplace Culture

AI needs to become part of the new culture, so it needs to be welcomed and be part of the team.  Fintechs should define clear roles for AI systems and have them complement human roles.  Recognizing AI and celebrating milestones can actually help employees see AI more as a partner than a threat, which builds up trust and collaboration instead of animosity.

See:  How AI is Revolutionizing Fintech

Companies should create an environment that encourages learning and adaptability. Innovation thrives on partnerships. By working with AI startups, academic institutions, and industry groups, fintechs can tap into new technologies and ideas. These collaborations can create a culture of experimentation, helping organizations to embrace innovative solutions that keep them ahead of their competition.

6. Create a Feedback Loop for Continuous Improvement

Do not just let AI systems operate on autopilot.  Establish real-time tracking metrics, such as cost savings, efficiency improvements, and customer satisfaction to monitor for high quality outputs, ethics, and adapt to changing needs. Conduct regular audits including by third parties to keep AI aligned with your priorities and business goals to ensure longer term effectiveness.

Outlook

Meta just announced plans to cut about 5% of its workforce targeting under performing employees, as part of a continual effort to improve efficiency in the age of AI.Both companies and employees should prepare for major changes that AI will bring.  Meta's setting the stage to replace mid-level engineers by 2025, will you be ready?

The National Crowdfunding & Fintech Association (NCFA Canada) is a financial innovation ecosystem that provides education, market intelligence, industry stewardship, networking and funding opportunities and services to thousands of community members and works closely with industry, government, partners and affiliates to create a vibrant and innovative fintech and funding industry in Canada. Decentralized and distributed, NCFA is engaged with global stakeholders and helps incubate projects and investment in fintech, alternative finance, crowdfunding, peer-to-peer finance, payments, digital assets and tokens, artificial intelligence, blockchain, cryptocurrency, regtech, and insurtech sectors. Join Canada's Fintech & Funding Community today FREE! Or become a contributing member and get perks. For more information, please visit: www.ncfacanada.org

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