My 3 interesting things for you this month…
1. Finding the right next place to work
If you’re looking for a new role in 2026, start by designing the right list of companies.
When most of us start looking for a new role, we head straight to job boards or recruiters. It feels productive, but it often leads to a scattergun process, lots of conversations and very little traction.
There’s a more effective approach I’m seeing work brilliantly with a handful of my clients right now (thanks to those readers/clients who shared their progress!), and AI can play a helpful role in it.
Instead of searching for roles, start by designing a short, intentional list of companies you would genuinely like to work for, then approach them directly.
Step 1: Get clear on what “right” actually means for you
Before you open any AI tool, take ten minutes to think and ask yourself:
- What values matter most to me at this stage of my career?
- What skills do I most enjoy using?
- What am I good at that the market values?
- What industries energise me rather than drain me?
- What problems do I want to help solve?
- What locations or working patterns are non-negotiable?
You’re doing this so you can give AI something concrete to work with, turning it from a novelty into a real leverage tool.
Step 2: Use AI to generate a targeted company list
Now you can ask AI to do the heavy lifting. The key is to be specific and structured in your prompt.
Here’s an example you can adapt:
“Act as a career research assistant for a senior finance professional.
Create a list of 20 UK-based companies I could proactively approach for a finance role.
My values are working for a great manager, flexibility and the potential to generate impact.
My strongest skills are commercial finance, stakeholder management and building great teams.
I’m interested in technology-enabled businesses, B2B services and scale-ups.
I want to work on problems related to growth, profitability and decision-making.
Prioritise companies with hybrid working and offices in London or the South East.”
Don’t worry if the first list isn’t perfect. The goal is a starting point that’s far more focused than a generic job search.
Step 3: Refine, don’t accept the first answer
Treat the first output as a draft. The quality improves quickly once you start asking questions.
Good follow-up prompts include:
- “Which of these companies are likely to be building or transforming their finance function?”
- “Remove companies that are highly bureaucratic or very hierarchical.”
- “Which of these would value a finance business partner rather than a traditional reporting role?”
- “Rank these companies by cultural fit based on the criteria above.”
Step 4: Research the problem before you approach
Once you have your shortlist, use AI again, but this time company by company.
Try:
- “What financial challenges is this company likely facing at its current stage?”
- “What would a strong finance leader need to focus on in the next 12 months here?”
- “What signals suggest this business may need more commercial finance capability?”
Doing this upfront means you arrive already thinking about what the business might be wrestling with, which completely changes how you show up in conversations.
Step 5: Approach with relevance, not a CV
When you reach out to hiring managers or senior leaders, lead with insight, not a job request.
Instead of:
“I’m looking for my next role and wondered if you’re hiring?”
Try:
“I’ve been following your growth over the last year and it looks like commercial decision-making and scaling finance capability will be critical. I’d love to share some perspectives and learn more about how you’re approaching it.”
AI won’t decide your next move for you, but used well, it can dramatically improve the quality of your thinking, focus and targeting.
2. Making your New Year goals a reality in 2026
Most goals fail because they’re too vague or too disconnected from real life.
Goals like “get better at leadership”, “improve work-life balance” or “develop commercially” are all well-intentioned, but they’re not very actionable.
A good goal turns into choices you can make week to week. This is how to get there.
Step one: Check the goal before you commit
A good goal should pass three tests:
1. It matters to you, not just your CV
If the goal exists just because it sounds sensible, it won’t survive a busy quarter. The best goals connect to frustration, curiosity or a genuine desire to change how you feel at work.
2. It focuses on direction, not perfection
Goals are signposts rather than promises. You’re deciding what to move towards, not defining an exact outcome.
3. It is within your influence
You can’t control promotions, restructures or market conditions. You can control skills you build, relationships you invest in and habits you create.
A simple check I often suggest is this: “If I made progress on this over the next six months, would my working life feel meaningfully different?” If the answer is no, it’s probably not the right goal.
Step two: Translate goals into behaviour
Once you have one to three clear goals, ask yourself a slightly uncomfortable question: “What would I actually be doing differently if this goal was working?”
For example:
- Leadership might show up in better 1:1s, clearer expectations and having the conversation you’ve been delaying.
- Career progression might show up as more time with commercial stakeholders, more visible work and stronger internal relationships.
- Wellbeing might show up as boundaries you keep, a calmer start and end to the day and fewer automatic yeses.
Step three: Use a 30 / 60 / 90 day execution lens
Think of the next 90 days as a short experiment.
The first 30 days: Create momentum
Focus on clarity and small wins. Ask:
- What do I need to stop, start or continue?
- What information, skills or conversations am I missing?
- What is the smallest action that moves this forward?
This phase is about removing friction and getting moving. If it already feels heavy, the goal is probably too big or too vague.
Days 31 to 60: Build consistency
This is the tricky stretch. The novelty wears off, work is busy again and there’s no immediate payoff.
This is exactly why this phase matters. Now ask:
- What does consistent progress look like weekly?
- Who needs to see or support this goal?
- What am I avoiding that would accelerate progress?
Execution here is about rhythm. Focus on what matters most: fewer actions, repeated more reliably.
Days 61 to 90: Apply and assess
The final phase is about application and feedback. Ask:
- Where am I seeing progress in real situations?
- What should I double down on or adjust?
- What evidence do I have that this is working?
By the end of 90 days, the useful question isn’t whether you “completed” the goal. It’s whether you’re moving in the right direction and whether the behaviours you chose are starting to stick.
That mindset matters, because long-term progress comes from what you repeat, not what you decide in January.
If all of this feels a bit much and you’d like some help, a coach can provide great accountability and bring the frameworks that will help you make progress. Get in touch – I still have a couple of coaching spaces left for January!
3. Making sense of AI progress: last year, this year and what comes next
It’s hard to open LinkedIn at the moment without someone claiming AI will change everything, or that it already has. Both are partly true and partly unhelpful.
For finance professionals, progress with AI is about understanding where the technology genuinely adds value right now, and what capabilities you and your team will need next.
A simple way to think about AI progress is in three stages.
2025: AI convenience
Over the last year, most people’s experience of AI has been about convenience: drafting emails, summarising documents, tidying slides and turning rough thoughts into something readable.
This has real value: it reduces friction and helps people get comfortable using the tools. The risk is assuming that’s the whole story and stopping there.
2026: AI efficiency
This year is about using AI to upskill yourself and your team so core finance processes run faster, more consistently and with fewer manual steps.
Think:
- Better use of the technology available to you
- More efficient month-end and reporting cycles
- Reduced rework and process cost
- Leveraging low cost and no cost tools and technology to do more with less
The focus here is capability building. Helping people ask better questions, validate outputs properly and use AI to improve how they work day to day.
Done well, this adds up. There’s an 84% chance you’ll free up around four hours per person, per month by adopting the techniques above.
2027: AI leverage
This is where AI becomes strategically interesting for finance.
As the technology continues to mature through the second half of this year and beyond, the real opportunity shifts from efficiency to leverage.
Examples include:
- Scenario modelling that genuinely shapes strategy
- Earlier identification of risks and opportunities
- More forward looking, decision led conversations with the business
- Finance moving from reporting history to shaping direction
The organisations that benefit most here will be the ones that invested earlier in skills, judgement and trust in the numbers.
AI progress doesn’t happen in one big jump. It comes in stages:
- Awareness: Convenience builds familiarity
- Upskilling: Efficiency builds capability
- Delegation: Leverage builds influence
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