Opportunities AI Creates for Early-Career Professionals

Marie May • June 25, 2025

Artificial Intelligence (AI) is rapidly transforming the workplace and early-career professionals are at the forefront of this change. As we continue to integrate AI into more aspects of business, it’s vital to understand how this technology will shape career paths, opportunities, and expectations for the next generation of talent… and support the transition before the skill gap widens any further.   


Leaders within our space have a responsibility to ensure early careers are supported within their organisations through well-structured onboarding programmes that ultimately offer a broader range of more advanced projects than entry level positions would typically offer. 


Is AI an Opportunity or a Challenge? 


The answer is both. The challenge being that there is a phasing out some traditional entry-level responsibilities. However, this opens the door to opportunities that have never been more exciting! 


How to Leverage the Opportunity 


1. Start Closer to the Core 

Traditionally, junior roles in data or analytics were focused on data entry, cleaning, or report generation. Today, AI tools like Python-based automation, data cleaning scripts, and platforms such as Dataiku or Alteryx streamline these tasks. 

This allows early-career professionals to: 

  • Participate in hypothesis design, stakeholder discussions, and model evaluations. 
  • Contribute to solving real-world problems early in their career. 
  • Gain exposure to the business impact of data from day one. 

2. Build Human-Centric Skills 

The World Economic Forum (2023) identifies analytical thinking, resilience, and emotional intelligence as some of the most in-demand skills. While AI excels at pattern recognition and prediction, it still lacks true creativity, empathy, and ethical judgment — areas where humans shine. 

Early-career professionals should: 

  • Hone their communication and storytelling skills. 
  • Learn how to translate data into decisions. 
  • Build cultural and ethical awareness to address bias in AI. 
3. Work Across Disciplines 

AI enables data fluency across domains. No longer siloed in IT, data roles now intersect with marketing, product development, HR, and more. This convergence empowers early professionals to: 

  • Rotate through departments. 
  • Collaborate on multi-disciplinary teams. 
  • Become T-shaped professionals - broad generalists with a deep skill in one area. 
4. Bring Fresh Perspectives 

Early-career professionals are uniquely positioned to: 

  • Spot emerging ethical risks that others overlook. 
  • Ask naïve questions that surface assumptions. 
  • Advocate for underrepresented users. 

This is particularly important as AI systems increasingly influence access to jobs, credit, education, and justice and this paid article from MIT on what is AI is a interesting guide

5. Become AI-Native Innovators 

According to the Deloitte 2025 Global Gen Z & Millennial Survey, Gen Z professionals - having grown up with digital tools - are often more comfortable experimenting with no-code platforms, AI assistants like ChatGPT, and collaborative tools. They are well-placed to: 

  • Automate routine workflows. 
  • Prototype internal tools. 
  • Innovate new solutions faster than their predecessors. 

Advice for Those Starting Out 
  1. Start building now: Use open datasets and platforms (Kaggle, Google Colab, GitHub) to build a portfolio. 
  2. Master the fundamentals: Focus on Python, SQL, and basic statistics. They're still the foundation. 
  3. Stay curious: Read broadly - not just technical AI, but ethics, policy, and user experience. 
  4. Find a mentor: Whether through LinkedIn, Slack communities, or local meetups, mentorship accelerates growth. 
  5. Contribute to open source: It’s a great way to learn, get noticed, and give back. 

Challenges to Watch 


Shrinking Entry-Level Tasks
Traditional ‘foot in the door’ roles involving admin, data entry, or scheduling are increasingly handled by AI raising the bar for first-job candidates, meaning young professionals must enter the workforce with a more advanced skill set or risk being left behind. 


Advice for Leadership 

To address this, organisations must take responsibility for keeping the early-career pipeline open. Leaders should design intentional pathways for skill development, embedding peer learning, mentorship, and real-world experience into workplace models. Without proactive leadership, the skills gap will continue to widen - stacking the odds against the next generation and weakening the long-term resilience of the workforce. 


Rising Expectations for AI Literacy


Today’s early career professionals are expected to be not just tech-savvy but AI-literate. Employers are looking for people who understand how to use AI tools effectively and ethically. This includes knowing when and how to use AI, interpreting results, and ensuring bias and misinformation are minimised. 


Advice for Leadership 

This growing expectation can be daunting, especially for those just entering the workforce. Leaders have a crucial role to play in bridging this gap. That means embedding AI training into onboarding and development programmes, fostering a culture of experimentation and learning, and making space for open dialogue about responsible AI use. By demystifying AI and supporting ongoing learning, organisations can empower the next generation to become confident, capable contributors in an AI-driven world. 


Rapid Change, Rising Uncertainty 


As AI tools evolve, job descriptions are shifting quickly. This constant change can create uncertainty for early-career workers, who may struggle to keep up with what’s expected or fear that their job might be automated. 


Advice for Leadership 

Leaders must recognise and respond to this uncertainty. That means clearly communicating how roles are evolving, providing pathways for continuous upskilling, and offering support structures that help individuals adapt. By fostering transparency, psychological safety, and a growth mindset, organisations can turn the anxiety of rapid change into a foundation for resilience and opportunity. 


Source Talent Who Are Ready to Grow with You 


Finding early-career professionals who are both qualified and ready to deliver from day one is a growing challenge. That’s where our Nurture Programme makes a difference. Designed for MSc students, it combines academic expertise with hands-on industry experience through live industry placements - equipping participants with the practical skills and confidence needed to make an immediate impact in the workplace. 


What is the Nurture Programme? 


The Nurture Programme is a three-month, live project experience designed to give graduates: 


  • Real-world exposure in a business-critical setting 
  • Opportunities to apply their theoretical knowledge 
  • Practical, hands-on skills in problem-solving, collaboration, and communication 

 

Bridging the Gap Between Education and Impact 


We also support organisations with graduate recruitment by connecting you with talented individuals who have just completed our Nurture Programme. 

Our graduates aren’t just fresh from their MSc studies, they’ve been immersed in live commercial projects, developed professional behaviours, and are eager to continue growing in a full-time role. 

By partnering with us, you gain access to a diverse pool of pre-vetted, motivated, and work-ready talent. 


Hire With Confidence 


  • Access a pool of graduates who’ve proven themselves on real projects 
  • Reduce onboarding time and training costs 
  • Support your early-careers strategy with impact-ready individuals 

 

Whether you’re filling entry-level roles or growing your graduate pipeline, we can connect you with talent that aligns with your goals. 


Final Thoughts 


The future of AI is not something to fear it’s something to prepare for. AI isn't eliminating entry-level roles - it's upgrading them. For those willing to adapt and learn, you will progress with a more interesting pathway than those who have gone before you. For early-career professionals, success will depend on a blend of curiosity, flexibility, and the willingness to evolve. Those who are proactive, digitally fluent, and emotionally intelligent will find that AI is not a threat, but a powerful ally in shaping a dynamic and fulfilling career. 


Let’s Connect 


Are you currently recruiting or planning to bring on graduate talent? 

Please get in touch to learn more about our Nurture Programme Alumni, we’d be delighted to introduce you to the next generation of high-potential professionals. 

Every career needs a strong start. Let’s build that beginning together. Reach out to Marie May to learn more about how we can support you to develop robust and diverse talent pipelines. 

 

 

 


By Christa Swain December 3, 2025
Executive Summary: AI, Ethics, and Human-Centred Design Our recent Leaders Advisory Board event - designed in partnership with Corndel - featured three engaging sessions that explored how AI impacts human cognition, customer experience, and fairness. Here's what we learnt: 1. Think or Sink – Are We Using AI to Enhance or Reduce Cognitive Ability? Speaker: Rosanne Werner , CEO at XcelerateIQ & ex Transformation Lead at Coca-Cola Roseanne opened the day with an interactive and thought-provoking session, firmly positioning AI: “AI should be your sparring partner, not your substitute for thinking.” Her research revealed a striking insight: 83% of people using LLMs couldn’t recall what they wrote, compared to just 11% using traditional search . The message? It’s not about avoiding AI, but using it in ways that strengthen thinking , not outsource it. Roseanne explained how our brains form engrams - memory footprints that enable creativity and critical thinking. Over-reliance on AI risks weakening these pathways, reducing retention and problem-solving ability. She introduced the Mind Over Machine Toolkit , six strategies to use AI as a thinking partner: Provide Context First – Frame the problem before asking AI. Use AI as a Challenger – Stress-test ideas and uncover blind spots. Iterative Co-Creation – Collaborate, refine, and evaluate. Document Your Thinking – Keep reasoning visible. Reflective Prompts – Support reflection, not replace judgment. Sparring Partner – Test assumptions and explore risks. Roseanne summed it up with a simple rule: use Sink for low-value, repetitive tasks, and Think for strategic, creative decisions. 2. Designing Chatbots with Human-Centred AI Speaker: Sarah Schlobohm , Fractional Chief AI Officer Sarah brought a practical perspective, drawing on experience implementing AI across sectors - from banking and cybersecurity to rail innovation. She began with a relatable question: “Who’s been frustrated by a chatbot recently?” Almost every hand went up. Through a real-world example (redacted out of politeness), Sarah illustrated how chatbots can fail when designed with the wrong priorities. The chatbot optimised for deflection and containment , but lacked escape routes , sentiment detection, and escalation paths - turning a simple purchase into a multi-day ordeal. “Don’t measure success by how well the chatbot performs for the bot—measure it by how well it performs for the human.” Sarah introduced principles for better chatbot design: Human-Centred Design – Focus on user needs and emotional impact. Systems Thinking – Consider the entire process, not just chatbot metrics. Escalation Triggers – Negative sentiment, repeated failures, high-value intents. Context Awareness – Detect when a task moves from routine to complex and route accordingly. The takeaway? Automation should remove friction from the whole system - not push it onto the customer. 3. Responsible AI and Bias in Large Language Models Speaker: Sarah Wyer , Professional Development Expert in AI Ethics at Corndel “When we create AI, we embed our values within it.” She shared her journey tackling gender bias in large language models , from GPT-2 through to GPT-5, and highlighted why responsible AI matters. AI systems reflect human choices - what data we use, how we define success, and who decides what is fair. Real-world examples brought this to life: facial recognition systems failing to recognise darker skin tones, credit decisions disadvantaging women, and risk assessment tools perpetuating racial bias. Even today, LinkedIn engagement patterns show gender bias! Sarah made the point that simple actions - like testing prompts such as “Women can…” or “Men can…” - can reveal hidden disparities and spark vital conversations. To address these issues, Sarah introduced the D.R.I.F.T framework , a practical guide for organisations: D – Diversity : Build diverse teams to challenge bias. R – Representative Data : Ensure datasets reflect all user groups. I – Independent/Internal Audit : Test outputs regularly. F – Freedom : Create a culture where employees can challenge AI decisions. T – Transparency : Share processes without exposing proprietary code. Wrapping up the final session - before we opened the floor to panel questions and debate - Sarah created the opportunity to discuss how we address AI bias within our organisations by stepping through the DRIFT framework. Shared Themes Across All Sessions AI is powerful, but context matters . Human oversight and ethical design are critical . Use AI to augment thinking , not replace it. Measure success by human outcomes , not just automation metrics. We've had such great feedback from this event series - especially around the quality of speakers and the opportunity to have meaningful conversation and debate outside of functions. Definitely more in the events plan for 2026! If you'd like to be part of the conversation please navigate to our LAB events page to register your interest .
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