5 Ways to Convince Your Manager to Fund Your Data and AI Training

According to a recent study by IBM, executives estimate that 40% of their workforce will need to reskill as a result of implementing AI over the next three years. 

Perhaps you've spotted an opportunity for data and AI upskilling, and you’re itching to get stuck in. You can already envisage the wondrous benefits for your team and your organisation. But, amidst the excitement, there’s a small voice reminding you that the first step is convincing your manager to fund your training.

Don’t worry, you’ve come to the right place! We’ll guide you on how to effectively communicate the remarkable benefits of data and AI upskilling for your organisation. If you want to get a definitive “yes” from your manager, keep reading.

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1. Create a business case for data upskilling

First things first, you want to create a business case. Essentially, this is your opportunity to show your manager just how beneficial data and AI upskilling can be for your organisation.

During your discussion, you may want to share some impactful data and AI stats like these:

  • According to a study by Accenture, 73% of global companies are prioritising AI over all other digital investments. 
  • Businesses surveyed in a BARC report and that use big data saw an average profit increase of 8%, and a 10% reduction in overall cost.
  • 91.9% of organisations achieved measurable value from data and analytics investments in 2023.

Fundamentally, you want to communicate how your upskilling will contribute towards achieving your organisation's most important goals. For instance, if your organisation focuses on increasing customer satisfaction, show how your upskilling will help reach this target.

Two women sat at desk talking with a laptop in between them

We’ll look at nailing the details of your specific business case in the next section. But for now, there are many benefits of upskilling in data and AI that your manager needs to hear! 

Here are some ideas to consider discussing to back your case: 

Increased efficiency and productivity

Mastering data and AI tools enables individuals to automate routine tasks, freeing up time for strategic work. 

Teams can streamline workflows and prioritise high-impact tasks. As efficiency improves across individuals and teams, operational costs drop, and projects are completed more quickly.

Take Elle Neal, for example, a former data scientist at BPA Quality. Elle saved her organisation 48 hours per month by switching from manual Excel spreadsheets to Python for data processing. She also simultaneously increased leads by 13 times. 

Enhanced decision-making

Employees trained in data analysis make informed, evidence-based decisions instead of relying solely on intuition. With enhanced analytical skills, teams identify data trends and insights that guide strategic planning and align projects with key objectives. 

This improved decision-making reduces costly mistakes, boosts profitability, and helps organisations remain competitive.

Innovation and problem solving

Individuals skilled in AI are often able to devise innovative solutions to business challenges by using predictive analytics and machine learning models. 

Teams can brainstorm and develop new products, processes, or strategies by leveraging their understanding of customer data and market trends. Data and AI-driven innovation promotes business growth, increases market share, and nurtures a culture of continuous improvement.

Improved customer satisfaction

Personalisation can lead to higher customer retention rates, increased sales, and a better reputation, ultimately driving long-term business growth. 

McKinsey reports that 71% of customers expect a personalised experience and 76% of consumers get frustrated if this doesn’t happen.

Data insights can be used to understand customer preferences. Teams across departments can then coordinate to create personalised, customer-centric strategies that boost customer satisfaction.

2. Nail the details

Not only do you need to emphasise the benefits that data and AI upskilling has generally, but also outline a detailed, case-specific action plan.

Your manager is more likely to agree to your upskilling if they can see you’ve put thought and consideration into the details.

Providing a plan lays out a path that makes it easier for managers to visualise how the training will happen. They’ll also be thankful that they don’t have to do the research themselves!

So what important details do you need to include in your outlined plan? 

  1. What’s the problem? - Firstly, identify the issues or opportunities within your team and organisation so your manager understands the challenges you're addressing. 

  2. How is this stopping us from reaching our goals? - Clearly link the issues to your organisation's objectives. Explain how inadequate data skills are preventing your organisation from reaching its targets.

  3. What skills are needed? - Outline what skills are needed to solve your team’s data issues or exploit the relevant opportunities. 

    For example, your team may need better data analysis skills to extract more insightful data. Or you may want to develop machine learning skills to help predict future demand.

  4. What’s the solution? - This is your opportunity to discuss upskilling solutions that will equip you with the necessary skills to address these issues. 

    You may want to talk about a few solutions and then highlight which you think would offer the best fit for your organisation and why.

  5. Who will need to upskill? - Review which team members would benefit most from upskilling. Demonstrate how upskilling a few individuals could facilitate broader team development. We'll explore this in more detail in the next section.

What to include in your upskilling plan of action infographic

3. Anticipate any objections

Even when you’ve prepared thoroughly and you’re armed with your new plan, your manager is still likely to have some questions or concerns. So be prepared to respond to these as soon as your manager raises them.

To be able to do this, firstly get into the mindset of your manager. If you were being approached by an employee about upskilling, what concerns would you initially have? Make a list and then write down notes on how to answer these queries.

We’ve put together some examples of questions your manager might ask and tips on how to answer these:

A. "Can you complete your regular work while doing this training?" 

If your manager asks this question you will need to reassure them that your regular duties will still be completed to the standards your employer expects.

You could approach this conversation with a well-considered answer that highlights the practicality of modern learning platforms and the flexibility these platforms offer. 

Most courses will also you to allocate specific hours each week for upskilling during times that best suit you. 

And additionally, you can reiterate that the skills that you’ll develop will help increase efficiency in the long run.

B. "How soon will you be able to apply what you've learned in practice?"

Many course providers will work with you to tailor your learnings to work- based projects. This means that projects you work on throughout your upskilling will be directly related to your job role, achieving great results for your organisation from the outset. 

When you research possible data upskilling solutions, this is something you’ll want your provider to clarify. 

Russell Johnson, Chief Data Scientist at Marks and Spencer

"I've seen the direct impact our data initiatives have had across various functions of our business. Our colleagues have been able to show a fast return on investment and extract more value from our data.” - Russell Johnson, Chief Data Scientist, Marks & Spencer.


C. "Can we share these skills internally without formal training?”

Here is your opportunity to discuss how upskilling one member of your team could lead to the upskilling of more of your employees. This is what is sometimes called a “hub-and-spoke” model.

In essence, the person who is being upskilled would act as the “hub” or knowledge expert in data or AI. And by sharing their knowledge with colleagues internally, those colleagues become empowered and more self-sufficient as “spokes”. 

Raising this with your manager could strengthen your case, even if they don’t ask the question. It can help them better understand how the organisation can get additional value out of upskilling just one member of the team. 

Imran Ayad, Data Analyst at Visa“My team saw the value of data science with Cambridge Spark. Being part of a global organisation such as Visa, teams in other regions would see the benefits of my projects and begin to reach out with enquiries. I would help them in building reports and dashboards relevant to their own unique requirements, as well as provide training to enable self-sufficiency going forward." - Imran Ayad, Data Analyst, Visa

4. Make it easy for your manager

You want to make this process as seamless and as easy for your manager as possible. If your manager is willing to take your plan to their seniors, they may need some additional information that will help to convince them.

After you’ve presented your plan, ask your manager if they’d like to see any additional information that would help them move forward with this upskilling proposal.

You should get any extra information to your manager as soon as possible, whilst the buzz of excitement and plan is fresh in their mind.

Woman sitting at desk on laptop with man standing behind pointing at the screen

Some additional information your manager may want to present to their seniors includes:

Monitoring effectiveness 

Outlining a plan for tracking progress and evaluating the impact on productivity could be very helpful for your manager and their seniors to see.

For example, you could propose setting specific benchmarks or key performance indicators (KPIs) before the training begins. 

These might include measures such as:

  • Reduced time on data-related tasks
  • Improved accuracy of data analyses
  • Increased number of projects completed using new AI tools

Presenting a structured approach to quantify upskilling's tangible benefits allows your manager to assure senior leaders that their investment is measurable and can yield great results!

Competitor analysis

Incorporating a competitor analysis can strengthen the case for investing in data and AI skills. You can gather information on how competitors are leveraging AI and data analytics to improve their operations and innovation tactics.

This demonstrates a clear industry trend towards data-driven decision making and the potential risk of being less competitive.

Costs and ROI

Your manager may want to see a detailed breakdown of the training costs, including any course fees, employee time allocation, and potential operational disruptions. 

You may also be asked to highlight the expected return on investment (ROI). This can be demonstrated by improved operational efficiency, cost reductions from automation, and potential income from new data-driven products or services.

5. Speak to your course provider

In some cases, your organisation may already work with a training provider that can support you with data upskilling. If so, you’ll want to speak to them first and gather any information that may help you build your plan and support your case.

If you don’t already have a course provider, you can still speak to potential training providers that offer relevant upskilling programmes.

You can talk to course providers about the data issues your team is currently experiencing and get the providers to explain how their courses will help you solve these issues and achieve your organisational goals. All this information is crucial when putting your case forward to your manager.

Woman on phone holding laptop walking down a corridor


Advocating for data and AI upskilling is a strategic investment that can present significant benefits for both you as an employee and your organisation as a whole.

Presenting a compelling business case and detailing a well-considered plan, whilst making the process as seamless as possible for your manager, can effectively communicate the value of upskilling.

This approach not only addresses current organisational challenges, but also positions the team to leverage advanced technologies for enhanced efficiency, decision-making, innovation, and customer satisfaction.

Ultimately, securing funding for such training is a step towards fostering a more competitive, forward-thinking business environment. 

If you’re interested in upskilling in data and AI, discover more about our Professional Programmes which can transform any team member into a data specialist in a matter of weeks. 

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