Behind on AI Workforce Readiness? Here Is Where to Start

Scott McCormick • 18 August 2026
Not every financial services firm planned this early. Most did not. If your AI programme is already live and the governance structure, the specialist capability or the right people are not fully in place yet, this article is for you. 

70%

of large-scale FS transformations miss their original objectives, most often due to people and capability gaps picked up too late

Is it too late if you have not planned ahead? 

No. But the approach changes. 


Planning ahead means building capability before you need it, hiring specialist roles before they become urgent, and designing governance structures before a programme goes live. Most firms are not in that position. 


Being behind does not mean being stuck. It means prioritising differently. The firms that recover well from a late start share one thing: they get honest about where the gaps actually are before they start filling them. 

The most expensive mistake is not starting late. It is starting late and then hiring reactively for the wrong things first. 

What should you do first if your programme is already live? 


Step 1: Name the gaps honestly before you try to fill them 


The instinct when a programme is under pressure is to hire quickly. But hiring fast for the wrong role, or the wrong level, costs more and takes longer to recover from than a brief pause to diagnose properly. 


Start with three questions. 

  1. Where is delivery actually at risk right now? 
  2. Which specific capability is missing, not which job title sounds right? 
  3. What does the person we need actually need to be able to do? 


Specificity here is everything. A firm that knows it needs a model risk manager who can hold a line between AI outputs and FCA compliance is in a very different position from one that knows it needs to hire someone in governance. 


Step 2: Separate what needs to be permanent from what needs to be fast 


Not every gap requires a permanent hire. Some of the most acute capability shortfalls in financial services AI programmes right now, AI governance lead cover, DORA programme management, model risk oversight, can be addressed with interim or contract resource while a permanent search runs in parallel. 


This is not a compromise. It is a deliberate approach. Interim resource buys you time to hire the right permanent person rather than the available one. 


Speed and quality are not always in conflict. But you have to be intentional about which gap needs which solution. 

Workforce Readiness for AI in Financial Services

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Step 3: Get your governance accountability named today, not next quarter 


If there is one thing that compounds more than anything else when it is unclear, it is AI governance ownership. Every week without a named, senior, authorised owner is a week where decisions are being made without proper accountability. 


This does not require a new hire immediately. It requires a decision. Who is accountable right now? Do they have the authority to act? Do they have a team? If the honest answer to any of those is no or not fully, that is the first gap to close. 


Step 4: Rebuild your hiring timeline with real numbers 


Three to six months is the realistic timeline for the roles that matter most. Model risk managers with AI experience. AI governance leads who understand FCA compliance. Change directors with DORA delivery background. 


If your programme plan has a capability gap that needs to be filled in six weeks, a permanent hire is unlikely to solve it. Knowing that now changes the options available to you. 


  • Map each open capability need against a realistic hiring timeline 
  • Identify which gaps can be bridged with interim or contract resource 
  • Start permanent searches immediately for roles with the longest lead times 
  • Brief your talent partner on the intersection skills, not just the job title 

 

Step 5: Use the pressure as a forcing function for better programme design 



Being behind on workforce readiness is uncomfortable. It is also, occasionally, useful. 


Firms that have been through the pressure of hiring specialist AI capability under urgency often come out with better workforce planning practices than those that never felt it. The lesson is visible and recent. The cost of getting it wrong is known. 


Use the current pressure to build the practices that prevent it happening again. Capability reviews at programme inception. Blended workforce models by design. AI governance placed deliberately, not by default. 

The firms that manage this well the second time are not necessarily the ones that got it right the first time. They are the ones that took the lessons from getting it wrong seriously enough to change how they plan. 

What does a realistic recovery look like? 


It depends on how wide the gap is and how much time the programme has. But the shape of a realistic recovery is usually the same. 


  • Honest diagnostic: which dimensions are most at risk and which have more runway 
  • Immediate governance clarity: name the accountable person and confirm their authority today 
  • Interim cover for the most urgent gaps while permanent searches run 
  • Parallel permanent searches for roles with long hiring timelines, started now 
  • Revised programme timelines that reflect realistic capability arrival dates, not optimistic ones 

 

None of this requires having planned ahead. It requires being honest about where you are now, and making deliberate decisions from that starting point rather than hoping the gap closes itself. 

Workforce Readiness for AI in Financial Services

If this raises questions about your own position, the full whitepaper goes further.


It covers the Execution Readiness Diagnostic, scorecard, readiness profiles and seven strategic questions.

Download Now
Frequently Asked Questions


What should a financial services firm do if it has not planned AI workforce readiness? 

Start with an honest diagnosis of which specific gaps carry the highest delivery risk. Separate what needs a permanent hire from what can be covered by interim resource while a permanent search runs. Name governance accountability today rather than next quarter. Then rebuild hiring timelines using realistic numbers, three to six months for most specialist AI roles. 


Can you recover from a late start on AI workforce readiness? 

Yes, but the approach is different from planning ahead. The priority is getting honest about the specific gaps before trying to fill them, using interim resource strategically to buy time for quality permanent hires, and making governance accountability explicit immediately rather than leaving it unclear. 


How long does it realistically take to hire specialist AI roles in financial services? 

Three to six months for the most in-demand profiles: model risk managers with AI context, AI governance leads with FCA compliance experience, and change directors with DORA delivery background. Knowing this changes how you approach gaps that need to be closed faster. 


How do I identify which AI workforce gaps are most urgent? 

Hydrogen Group's Execution Readiness Diagnostic, included in the full whitepaper, scores organisations across five dimensions: strategic clarity, delivery capacity, specialist capability, AI governance and leadership alignment. It surfaces the specific dimensions carrying the highest delivery risk and helps prioritise where to act first. 

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