Who should get a PAIR license?
How to improve AI ROI without increasing spend
Who should get a PAIR license?
Written by
Director of AI Adoption
Working out who should get what sort of LLM license is a new and high-stakes challenge for organisations trying to adopt AI. Particularly difficult is deciding between the free tiers of ChatGPT, Copilot or Claude, paid tiers that might cost $20-40 per month a month, and pro tiers that can run upwards of $200. With 100s or 1,000s of users costs add up fast, and while for some staff a paid license is a nice-to-have, for others it can unlock transformative productivity. Getting this right can be the difference between an AI rollout that succeeds and one that stalls.
Lots of the obvious solutions have big downsides. ‘First come first serve’ and ‘use it or lose it’ models are straightforward but risk leaving behind any staff who are coming to AI more slowly. Many of these later-adopters would be the among the biggest beneficiaries from AI: just think of the acceleration for a non-technical employee suddenly learning how to steer a superhuman coder-analyst in plain English. Assigning licenses to management-designated ‘super users’ suffers from a similar problem: guesses about who will get the most out of AI are often plain wrong. At Pair time and again we see many managers (pleasantly!) surprised at who in their teams achieve AI mastery first.
We think it’s possible to do better, and we’ve been working hard to turn these LLM license provisioning decisions into something that happens fairly and organically. We think everyone should have the chance to access the most advanced LLM features available within their organisation, especially if they’ve proved their competence to use them. At the same time, there’s no point paying for a premium license for a user who hasn’t got to those advanced features yet.
So this is what we’ve built into the admin dashboard on the Pair platform: a ‘license allocation helper’. Pair certification has become a very strong predictor – and driver – of advanced LLM use: users who achieve Mastery are ~15× more likely to use advanced features than those who aren’t certified.
Pictured: the Pair license allocation helper. The upgrade and downgrade suggestions are based on your criteria and can be exported directly to CSV.
The license allocation helper takes advantage of this, first by letting Pair admins see who has a free-tier license today, and then out of this group who has proven their AI capability by progressing furthest through the hands-on AI Masterclasses. Users above a capability threshold (and organisations can pick the level that makes sense to them) are then automatically identified for an upgrade.
Conversely, users with premium licenses who aren’t yet ready to make the most of LLM’s more advanced capabilities can be flagged to move back to the free tier. Unlike ‘use it or lose it’, which can bring a novice user’s AI journey to an end with a bump, this isn’t a one-way street. All they need to do is work through the masterclasses and when they’re ready, they can be upgraded back to the paid tier.
We hope that balancing these two groups can increase your ROI from the licenses you’re paying for, without increasing spend, in a way that’s fair, easy to explain and easy to administer:
More articles
Friday, February 6, 2026
Written by
Elena Bergmann
How AI reverses the digital skills gap
If organisations build the right adoption infrastructure first
For forty years, every digital transformation created a new technical elite. ERP systems in the 1990s. Cloud infrastructure in the 2010s. Each wave demanded increasingly specialised knowledge and widened the gap between those who could speak to machines and those who couldn't. But AI is finally breaking that pattern, offering a genuine opportunity to close the divide rather than widen it.
Friday, October 24, 2025
Written by
Elena Bergmann
From Operators to Orchestrators
Why curation, evaluation & narration will define high-performance careers in the age of AI
The smartest executives I know aren't asking whether to adopt AI – they're asking how to become irreplaceable because of it.
Friday, September 26, 2025
Written by
Anne Kuhsiek
How a traditional wholesaler became an AI pioneer in six months
Regal Wholesale's journey from spreadsheet searches to custom AI agents, powered by the Wirral AI Academy
Regal Wholesale is an award-winning, family-run brand distribution and wholesale business, widely regarded as the No.1 distributor of paper hygiene products across the UK, with a growing international footprint. Facing increasing customer expectations and growing competition, Regal launched a company-wide digital transformation spanning CRM improvements to ISO certifications. But their participation in the Wirral AI Academy, powered by PAIR, unlocked something different.
Monday, September 22, 2025
Written by
Anne Kuhsiek
Wirral AI Academy Impact Report
Embedding AI into everyday work
On-the-ground results of how businesses in the Wirral are adopting AI – from early experimentation to embedded change – and what it means for the future of their community.
Friday, August 8, 2025
Written by
Anne Kuhsiek
AI, One Step at a Time
Real stories from SMEs embracing AI to work smarter, not harder
Curious how AI can fit into your team’s workflow? Hear directly from Wirral businesses who’ve made it part of their daily operations, and why they’re not looking back.
Who should get a PAIR license?
How to improve AI ROI without increasing spend
Who should get a PAIR license?
Written by
Director of AI Adoption
Working out who should get what sort of LLM license is a new and high-stakes challenge for organisations trying to adopt AI. Particularly difficult is deciding between the free tiers of ChatGPT, Copilot or Claude, paid tiers that might cost $20-40 per month a month, and pro tiers that can run upwards of $200. With 100s or 1,000s of users costs add up fast, and while for some staff a paid license is a nice-to-have, for others it can unlock transformative productivity. Getting this right can be the difference between an AI rollout that succeeds and one that stalls.
Lots of the obvious solutions have big downsides. ‘First come first serve’ and ‘use it or lose it’ models are straightforward but risk leaving behind any staff who are coming to AI more slowly. Many of these later-adopters would be the among the biggest beneficiaries from AI: just think of the acceleration for a non-technical employee suddenly learning how to steer a superhuman coder-analyst in plain English. Assigning licenses to management-designated ‘super users’ suffers from a similar problem: guesses about who will get the most out of AI are often plain wrong. At Pair time and again we see many managers (pleasantly!) surprised at who in their teams achieve AI mastery first.
We think it’s possible to do better, and we’ve been working hard to turn these LLM license provisioning decisions into something that happens fairly and organically. We think everyone should have the chance to access the most advanced LLM features available within their organisation, especially if they’ve proved their competence to use them. At the same time, there’s no point paying for a premium license for a user who hasn’t got to those advanced features yet.
So this is what we’ve built into the admin dashboard on the Pair platform: a ‘license allocation helper’. Pair certification has become a very strong predictor – and driver – of advanced LLM use: users who achieve Mastery are ~15× more likely to use advanced features than those who aren’t certified.
Pictured: the Pair license allocation helper. The upgrade and downgrade suggestions are based on your criteria and can be exported directly to CSV.
The license allocation helper takes advantage of this, first by letting Pair admins see who has a free-tier license today, and then out of this group who has proven their AI capability by progressing furthest through the hands-on AI Masterclasses. Users above a capability threshold (and organisations can pick the level that makes sense to them) are then automatically identified for an upgrade.
Conversely, users with premium licenses who aren’t yet ready to make the most of LLM’s more advanced capabilities can be flagged to move back to the free tier. Unlike ‘use it or lose it’, which can bring a novice user’s AI journey to an end with a bump, this isn’t a one-way street. All they need to do is work through the masterclasses and when they’re ready, they can be upgraded back to the paid tier.
We hope that balancing these two groups can increase your ROI from the licenses you’re paying for, without increasing spend, in a way that’s fair, easy to explain and easy to administer:
More articles
How AI reverses the digital skills gap
If organisations build the right adoption infrastructure first
From Operators to Orchestrators
Why curation, evaluation & narration will define high-performance careers in the age of AI
How a traditional wholesaler became an AI pioneer in six months
Regal Wholesale's journey from spreadsheet searches to custom AI agents, powered by the Wirral AI Academy
Wirral AI Academy Impact Report
Embedding AI into everyday work
AI, One Step at a Time
Real stories from SMEs embracing AI to work smarter, not harder
Who should get a PAIR license?
How to improve AI ROI without increasing spend
Who should get a PAIR license?
Written by
Director of AI Adoption
Working out who should get what sort of LLM license is a new and high-stakes challenge for organisations trying to adopt AI. Particularly difficult is deciding between the free tiers of ChatGPT, Copilot or Claude, paid tiers that might cost $20-40 per month a month, and pro tiers that can run upwards of $200. With 100s or 1,000s of users costs add up fast, and while for some staff a paid license is a nice-to-have, for others it can unlock transformative productivity. Getting this right can be the difference between an AI rollout that succeeds and one that stalls.
Lots of the obvious solutions have big downsides. ‘First come first serve’ and ‘use it or lose it’ models are straightforward but risk leaving behind any staff who are coming to AI more slowly. Many of these later-adopters would be the among the biggest beneficiaries from AI: just think of the acceleration for a non-technical employee suddenly learning how to steer a superhuman coder-analyst in plain English. Assigning licenses to management-designated ‘super users’ suffers from a similar problem: guesses about who will get the most out of AI are often plain wrong. At Pair time and again we see many managers (pleasantly!) surprised at who in their teams achieve AI mastery first.
We think it’s possible to do better, and we’ve been working hard to turn these LLM license provisioning decisions into something that happens fairly and organically. We think everyone should have the chance to access the most advanced LLM features available within their organisation, especially if they’ve proved their competence to use them. At the same time, there’s no point paying for a premium license for a user who hasn’t got to those advanced features yet.
So this is what we’ve built into the admin dashboard on the Pair platform: a ‘license allocation helper’. Pair certification has become a very strong predictor – and driver – of advanced LLM use: users who achieve Mastery are ~15× more likely to use advanced features than those who aren’t certified.
Pictured: the Pair license allocation helper. The upgrade and downgrade suggestions are based on your criteria and can be exported directly to CSV.
The license allocation helper takes advantage of this, first by letting Pair admins see who has a free-tier license today, and then out of this group who has proven their AI capability by progressing furthest through the hands-on AI Masterclasses. Users above a capability threshold (and organisations can pick the level that makes sense to them) are then automatically identified for an upgrade.
Conversely, users with premium licenses who aren’t yet ready to make the most of LLM’s more advanced capabilities can be flagged to move back to the free tier. Unlike ‘use it or lose it’, which can bring a novice user’s AI journey to an end with a bump, this isn’t a one-way street. All they need to do is work through the masterclasses and when they’re ready, they can be upgraded back to the paid tier.
We hope that balancing these two groups can increase your ROI from the licenses you’re paying for, without increasing spend, in a way that’s fair, easy to explain and easy to administer:
More articles
How AI reverses the digital skills gap
If organisations build the right adoption infrastructure first
From Operators to Orchestrators
Why curation, evaluation & narration will define high-performance careers in the age of AI
How a traditional wholesaler became an AI pioneer in six months
Regal Wholesale's journey from spreadsheet searches to custom AI agents, powered by the Wirral AI Academy
Wirral AI Academy Impact Report
Embedding AI into everyday work
AI, One Step at a Time
Real stories from SMEs embracing AI to work smarter, not harder
Do your best work faster with AI
Book a short session to see how Pair fits your organisation
Who should get a PAIR license?
How to improve AI ROI without increasing spend
Who should get a PAIR license?
Written by
Director of AI Adoption
Working out who should get what sort of LLM license is a new and high-stakes challenge for organisations trying to adopt AI. Particularly difficult is deciding between the free tiers of ChatGPT, Copilot or Claude, paid tiers that might cost $20-40 per month a month, and pro tiers that can run upwards of $200. With 100s or 1,000s of users costs add up fast, and while for some staff a paid license is a nice-to-have, for others it can unlock transformative productivity. Getting this right can be the difference between an AI rollout that succeeds and one that stalls.
Lots of the obvious solutions have big downsides. ‘First come first serve’ and ‘use it or lose it’ models are straightforward but risk leaving behind any staff who are coming to AI more slowly. Many of these later-adopters would be the among the biggest beneficiaries from AI: just think of the acceleration for a non-technical employee suddenly learning how to steer a superhuman coder-analyst in plain English. Assigning licenses to management-designated ‘super users’ suffers from a similar problem: guesses about who will get the most out of AI are often plain wrong. At Pair time and again we see many managers (pleasantly!) surprised at who in their teams achieve AI mastery first.
We think it’s possible to do better, and we’ve been working hard to turn these LLM license provisioning decisions into something that happens fairly and organically. We think everyone should have the chance to access the most advanced LLM features available within their organisation, especially if they’ve proved their competence to use them. At the same time, there’s no point paying for a premium license for a user who hasn’t got to those advanced features yet.
So this is what we’ve built into the admin dashboard on the Pair platform: a ‘license allocation helper’. Pair certification has become a very strong predictor – and driver – of advanced LLM use: users who achieve Mastery are ~15× more likely to use advanced features than those who aren’t certified.
Pictured: the Pair license allocation helper. The upgrade and downgrade suggestions are based on your criteria and can be exported directly to CSV.
The license allocation helper takes advantage of this, first by letting Pair admins see who has a free-tier license today, and then out of this group who has proven their AI capability by progressing furthest through the hands-on AI Masterclasses. Users above a capability threshold (and organisations can pick the level that makes sense to them) are then automatically identified for an upgrade.
Conversely, users with premium licenses who aren’t yet ready to make the most of LLM’s more advanced capabilities can be flagged to move back to the free tier. Unlike ‘use it or lose it’, which can bring a novice user’s AI journey to an end with a bump, this isn’t a one-way street. All they need to do is work through the masterclasses and when they’re ready, they can be upgraded back to the paid tier.
We hope that balancing these two groups can increase your ROI from the licenses you’re paying for, without increasing spend, in a way that’s fair, easy to explain and easy to administer:
More articles
Friday, February 6, 2026
Written by
Elena Bergmann
How AI reverses the digital skills gap
If organisations build the right adoption infrastructure first
For forty years, every digital transformation created a new technical elite. ERP systems in the 1990s. Cloud infrastructure in the 2010s. Each wave demanded increasingly specialised knowledge and widened the gap between those who could speak to machines and those who couldn't. But AI is finally breaking that pattern, offering a genuine opportunity to close the divide rather than widen it.
Friday, October 24, 2025
Written by
Elena Bergmann
From Operators to Orchestrators
Why curation, evaluation & narration will define high-performance careers in the age of AI
The smartest executives I know aren't asking whether to adopt AI – they're asking how to become irreplaceable because of it.
Friday, September 26, 2025
Written by
Anne Kuhsiek
How a traditional wholesaler became an AI pioneer in six months
Regal Wholesale's journey from spreadsheet searches to custom AI agents, powered by the Wirral AI Academy
Regal Wholesale is an award-winning, family-run brand distribution and wholesale business, widely regarded as the No.1 distributor of paper hygiene products across the UK, with a growing international footprint. Facing increasing customer expectations and growing competition, Regal launched a company-wide digital transformation spanning CRM improvements to ISO certifications. But their participation in the Wirral AI Academy, powered by PAIR, unlocked something different.
Monday, September 22, 2025
Written by
Anne Kuhsiek
Wirral AI Academy Impact Report
Embedding AI into everyday work
On-the-ground results of how businesses in the Wirral are adopting AI – from early experimentation to embedded change – and what it means for the future of their community.
Friday, August 8, 2025
Written by
Anne Kuhsiek
AI, One Step at a Time
Real stories from SMEs embracing AI to work smarter, not harder
Curious how AI can fit into your team’s workflow? Hear directly from Wirral businesses who’ve made it part of their daily operations, and why they’re not looking back.
Who should get a PAIR license?
How to improve AI ROI without increasing spend
Who should get a PAIR license?
Written by
Director of AI Adoption
Working out who should get what sort of LLM license is a new and high-stakes challenge for organisations trying to adopt AI. Particularly difficult is deciding between the free tiers of ChatGPT, Copilot or Claude, paid tiers that might cost $20-40 per month a month, and pro tiers that can run upwards of $200. With 100s or 1,000s of users costs add up fast, and while for some staff a paid license is a nice-to-have, for others it can unlock transformative productivity. Getting this right can be the difference between an AI rollout that succeeds and one that stalls.
Lots of the obvious solutions have big downsides. ‘First come first serve’ and ‘use it or lose it’ models are straightforward but risk leaving behind any staff who are coming to AI more slowly. Many of these later-adopters would be the among the biggest beneficiaries from AI: just think of the acceleration for a non-technical employee suddenly learning how to steer a superhuman coder-analyst in plain English. Assigning licenses to management-designated ‘super users’ suffers from a similar problem: guesses about who will get the most out of AI are often plain wrong. At Pair time and again we see many managers (pleasantly!) surprised at who in their teams achieve AI mastery first.
We think it’s possible to do better, and we’ve been working hard to turn these LLM license provisioning decisions into something that happens fairly and organically. We think everyone should have the chance to access the most advanced LLM features available within their organisation, especially if they’ve proved their competence to use them. At the same time, there’s no point paying for a premium license for a user who hasn’t got to those advanced features yet.
So this is what we’ve built into the admin dashboard on the Pair platform: a ‘license allocation helper’. Pair certification has become a very strong predictor – and driver – of advanced LLM use: users who achieve Mastery are ~15× more likely to use advanced features than those who aren’t certified.
Pictured: the Pair license allocation helper. The upgrade and downgrade suggestions are based on your criteria and can be exported directly to CSV.
The license allocation helper takes advantage of this, first by letting Pair admins see who has a free-tier license today, and then out of this group who has proven their AI capability by progressing furthest through the hands-on AI Masterclasses. Users above a capability threshold (and organisations can pick the level that makes sense to them) are then automatically identified for an upgrade.
Conversely, users with premium licenses who aren’t yet ready to make the most of LLM’s more advanced capabilities can be flagged to move back to the free tier. Unlike ‘use it or lose it’, which can bring a novice user’s AI journey to an end with a bump, this isn’t a one-way street. All they need to do is work through the masterclasses and when they’re ready, they can be upgraded back to the paid tier.
We hope that balancing these two groups can increase your ROI from the licenses you’re paying for, without increasing spend, in a way that’s fair, easy to explain and easy to administer:
More articles
How AI reverses the digital skills gap
If organisations build the right adoption infrastructure first
From Operators to Orchestrators
Why curation, evaluation & narration will define high-performance careers in the age of AI
How a traditional wholesaler became an AI pioneer in six months
Regal Wholesale's journey from spreadsheet searches to custom AI agents, powered by the Wirral AI Academy
Wirral AI Academy Impact Report
Embedding AI into everyday work
AI, One Step at a Time
Real stories from SMEs embracing AI to work smarter, not harder
Who should get a PAIR license?
How to improve AI ROI without increasing spend
Who should get a PAIR license?
Written by
Director of AI Adoption
Working out who should get what sort of LLM license is a new and high-stakes challenge for organisations trying to adopt AI. Particularly difficult is deciding between the free tiers of ChatGPT, Copilot or Claude, paid tiers that might cost $20-40 per month a month, and pro tiers that can run upwards of $200. With 100s or 1,000s of users costs add up fast, and while for some staff a paid license is a nice-to-have, for others it can unlock transformative productivity. Getting this right can be the difference between an AI rollout that succeeds and one that stalls.
Lots of the obvious solutions have big downsides. ‘First come first serve’ and ‘use it or lose it’ models are straightforward but risk leaving behind any staff who are coming to AI more slowly. Many of these later-adopters would be the among the biggest beneficiaries from AI: just think of the acceleration for a non-technical employee suddenly learning how to steer a superhuman coder-analyst in plain English. Assigning licenses to management-designated ‘super users’ suffers from a similar problem: guesses about who will get the most out of AI are often plain wrong. At Pair time and again we see many managers (pleasantly!) surprised at who in their teams achieve AI mastery first.
We think it’s possible to do better, and we’ve been working hard to turn these LLM license provisioning decisions into something that happens fairly and organically. We think everyone should have the chance to access the most advanced LLM features available within their organisation, especially if they’ve proved their competence to use them. At the same time, there’s no point paying for a premium license for a user who hasn’t got to those advanced features yet.
So this is what we’ve built into the admin dashboard on the Pair platform: a ‘license allocation helper’. Pair certification has become a very strong predictor – and driver – of advanced LLM use: users who achieve Mastery are ~15× more likely to use advanced features than those who aren’t certified.
Pictured: the Pair license allocation helper. The upgrade and downgrade suggestions are based on your criteria and can be exported directly to CSV.
The license allocation helper takes advantage of this, first by letting Pair admins see who has a free-tier license today, and then out of this group who has proven their AI capability by progressing furthest through the hands-on AI Masterclasses. Users above a capability threshold (and organisations can pick the level that makes sense to them) are then automatically identified for an upgrade.
Conversely, users with premium licenses who aren’t yet ready to make the most of LLM’s more advanced capabilities can be flagged to move back to the free tier. Unlike ‘use it or lose it’, which can bring a novice user’s AI journey to an end with a bump, this isn’t a one-way street. All they need to do is work through the masterclasses and when they’re ready, they can be upgraded back to the paid tier.
We hope that balancing these two groups can increase your ROI from the licenses you’re paying for, without increasing spend, in a way that’s fair, easy to explain and easy to administer:
More articles
How AI reverses the digital skills gap
If organisations build the right adoption infrastructure first
From Operators to Orchestrators
Why curation, evaluation & narration will define high-performance careers in the age of AI
How a traditional wholesaler became an AI pioneer in six months
Regal Wholesale's journey from spreadsheet searches to custom AI agents, powered by the Wirral AI Academy
Wirral AI Academy Impact Report
Embedding AI into everyday work
AI, One Step at a Time
Real stories from SMEs embracing AI to work smarter, not harder
Do your best work faster with AI
Book a short session to see how Pair fits your organisation
Who should get a PAIR license?
How to improve AI ROI without increasing spend
Who should get a PAIR license?
Written by
Director of AI Adoption
Working out who should get what sort of LLM license is a new and high-stakes challenge for organisations trying to adopt AI. Particularly difficult is deciding between the free tiers of ChatGPT, Copilot or Claude, paid tiers that might cost $20-40 per month a month, and pro tiers that can run upwards of $200. With 100s or 1,000s of users costs add up fast, and while for some staff a paid license is a nice-to-have, for others it can unlock transformative productivity. Getting this right can be the difference between an AI rollout that succeeds and one that stalls.
Lots of the obvious solutions have big downsides. ‘First come first serve’ and ‘use it or lose it’ models are straightforward but risk leaving behind any staff who are coming to AI more slowly. Many of these later-adopters would be the among the biggest beneficiaries from AI: just think of the acceleration for a non-technical employee suddenly learning how to steer a superhuman coder-analyst in plain English. Assigning licenses to management-designated ‘super users’ suffers from a similar problem: guesses about who will get the most out of AI are often plain wrong. At Pair time and again we see many managers (pleasantly!) surprised at who in their teams achieve AI mastery first.
We think it’s possible to do better, and we’ve been working hard to turn these LLM license provisioning decisions into something that happens fairly and organically. We think everyone should have the chance to access the most advanced LLM features available within their organisation, especially if they’ve proved their competence to use them. At the same time, there’s no point paying for a premium license for a user who hasn’t got to those advanced features yet.
So this is what we’ve built into the admin dashboard on the Pair platform: a ‘license allocation helper’. Pair certification has become a very strong predictor – and driver – of advanced LLM use: users who achieve Mastery are ~15× more likely to use advanced features than those who aren’t certified.
Pictured: the Pair license allocation helper. The upgrade and downgrade suggestions are based on your criteria and can be exported directly to CSV.
The license allocation helper takes advantage of this, first by letting Pair admins see who has a free-tier license today, and then out of this group who has proven their AI capability by progressing furthest through the hands-on AI Masterclasses. Users above a capability threshold (and organisations can pick the level that makes sense to them) are then automatically identified for an upgrade.
Conversely, users with premium licenses who aren’t yet ready to make the most of LLM’s more advanced capabilities can be flagged to move back to the free tier. Unlike ‘use it or lose it’, which can bring a novice user’s AI journey to an end with a bump, this isn’t a one-way street. All they need to do is work through the masterclasses and when they’re ready, they can be upgraded back to the paid tier.
We hope that balancing these two groups can increase your ROI from the licenses you’re paying for, without increasing spend, in a way that’s fair, easy to explain and easy to administer:
More articles
Friday, February 6, 2026
Written by
Elena Bergmann
How AI reverses the digital skills gap
If organisations build the right adoption infrastructure first
For forty years, every digital transformation created a new technical elite. ERP systems in the 1990s. Cloud infrastructure in the 2010s. Each wave demanded increasingly specialised knowledge and widened the gap between those who could speak to machines and those who couldn't. But AI is finally breaking that pattern, offering a genuine opportunity to close the divide rather than widen it.
Friday, October 24, 2025
Written by
Elena Bergmann
From Operators to Orchestrators
Why curation, evaluation & narration will define high-performance careers in the age of AI
The smartest executives I know aren't asking whether to adopt AI – they're asking how to become irreplaceable because of it.
Friday, September 26, 2025
Written by
Anne Kuhsiek
How a traditional wholesaler became an AI pioneer in six months
Regal Wholesale's journey from spreadsheet searches to custom AI agents, powered by the Wirral AI Academy
Regal Wholesale is an award-winning, family-run brand distribution and wholesale business, widely regarded as the No.1 distributor of paper hygiene products across the UK, with a growing international footprint. Facing increasing customer expectations and growing competition, Regal launched a company-wide digital transformation spanning CRM improvements to ISO certifications. But their participation in the Wirral AI Academy, powered by PAIR, unlocked something different.
Monday, September 22, 2025
Written by
Anne Kuhsiek
Wirral AI Academy Impact Report
Embedding AI into everyday work
On-the-ground results of how businesses in the Wirral are adopting AI – from early experimentation to embedded change – and what it means for the future of their community.
Friday, August 8, 2025
Written by
Anne Kuhsiek
AI, One Step at a Time
Real stories from SMEs embracing AI to work smarter, not harder
Curious how AI can fit into your team’s workflow? Hear directly from Wirral businesses who’ve made it part of their daily operations, and why they’re not looking back.
Who should get a PAIR license?
How to improve AI ROI without increasing spend
Who should get a PAIR license?
Written by
Director of AI Adoption
Working out who should get what sort of LLM license is a new and high-stakes challenge for organisations trying to adopt AI. Particularly difficult is deciding between the free tiers of ChatGPT, Copilot or Claude, paid tiers that might cost $20-40 per month a month, and pro tiers that can run upwards of $200. With 100s or 1,000s of users costs add up fast, and while for some staff a paid license is a nice-to-have, for others it can unlock transformative productivity. Getting this right can be the difference between an AI rollout that succeeds and one that stalls.
Lots of the obvious solutions have big downsides. ‘First come first serve’ and ‘use it or lose it’ models are straightforward but risk leaving behind any staff who are coming to AI more slowly. Many of these later-adopters would be the among the biggest beneficiaries from AI: just think of the acceleration for a non-technical employee suddenly learning how to steer a superhuman coder-analyst in plain English. Assigning licenses to management-designated ‘super users’ suffers from a similar problem: guesses about who will get the most out of AI are often plain wrong. At Pair time and again we see many managers (pleasantly!) surprised at who in their teams achieve AI mastery first.
We think it’s possible to do better, and we’ve been working hard to turn these LLM license provisioning decisions into something that happens fairly and organically. We think everyone should have the chance to access the most advanced LLM features available within their organisation, especially if they’ve proved their competence to use them. At the same time, there’s no point paying for a premium license for a user who hasn’t got to those advanced features yet.
So this is what we’ve built into the admin dashboard on the Pair platform: a ‘license allocation helper’. Pair certification has become a very strong predictor – and driver – of advanced LLM use: users who achieve Mastery are ~15× more likely to use advanced features than those who aren’t certified.
Pictured: the Pair license allocation helper. The upgrade and downgrade suggestions are based on your criteria and can be exported directly to CSV.
The license allocation helper takes advantage of this, first by letting Pair admins see who has a free-tier license today, and then out of this group who has proven their AI capability by progressing furthest through the hands-on AI Masterclasses. Users above a capability threshold (and organisations can pick the level that makes sense to them) are then automatically identified for an upgrade.
Conversely, users with premium licenses who aren’t yet ready to make the most of LLM’s more advanced capabilities can be flagged to move back to the free tier. Unlike ‘use it or lose it’, which can bring a novice user’s AI journey to an end with a bump, this isn’t a one-way street. All they need to do is work through the masterclasses and when they’re ready, they can be upgraded back to the paid tier.
We hope that balancing these two groups can increase your ROI from the licenses you’re paying for, without increasing spend, in a way that’s fair, easy to explain and easy to administer:
More articles
How AI reverses the digital skills gap
If organisations build the right adoption infrastructure first
From Operators to Orchestrators
Why curation, evaluation & narration will define high-performance careers in the age of AI
How a traditional wholesaler became an AI pioneer in six months
Regal Wholesale's journey from spreadsheet searches to custom AI agents, powered by the Wirral AI Academy
Wirral AI Academy Impact Report
Embedding AI into everyday work
AI, One Step at a Time
Real stories from SMEs embracing AI to work smarter, not harder
Who should get a PAIR license?
How to improve AI ROI without increasing spend
Who should get a PAIR license?
Written by
Director of AI Adoption
Working out who should get what sort of LLM license is a new and high-stakes challenge for organisations trying to adopt AI. Particularly difficult is deciding between the free tiers of ChatGPT, Copilot or Claude, paid tiers that might cost $20-40 per month a month, and pro tiers that can run upwards of $200. With 100s or 1,000s of users costs add up fast, and while for some staff a paid license is a nice-to-have, for others it can unlock transformative productivity. Getting this right can be the difference between an AI rollout that succeeds and one that stalls.
Lots of the obvious solutions have big downsides. ‘First come first serve’ and ‘use it or lose it’ models are straightforward but risk leaving behind any staff who are coming to AI more slowly. Many of these later-adopters would be the among the biggest beneficiaries from AI: just think of the acceleration for a non-technical employee suddenly learning how to steer a superhuman coder-analyst in plain English. Assigning licenses to management-designated ‘super users’ suffers from a similar problem: guesses about who will get the most out of AI are often plain wrong. At Pair time and again we see many managers (pleasantly!) surprised at who in their teams achieve AI mastery first.
We think it’s possible to do better, and we’ve been working hard to turn these LLM license provisioning decisions into something that happens fairly and organically. We think everyone should have the chance to access the most advanced LLM features available within their organisation, especially if they’ve proved their competence to use them. At the same time, there’s no point paying for a premium license for a user who hasn’t got to those advanced features yet.
So this is what we’ve built into the admin dashboard on the Pair platform: a ‘license allocation helper’. Pair certification has become a very strong predictor – and driver – of advanced LLM use: users who achieve Mastery are ~15× more likely to use advanced features than those who aren’t certified.
Pictured: the Pair license allocation helper. The upgrade and downgrade suggestions are based on your criteria and can be exported directly to CSV.
The license allocation helper takes advantage of this, first by letting Pair admins see who has a free-tier license today, and then out of this group who has proven their AI capability by progressing furthest through the hands-on AI Masterclasses. Users above a capability threshold (and organisations can pick the level that makes sense to them) are then automatically identified for an upgrade.
Conversely, users with premium licenses who aren’t yet ready to make the most of LLM’s more advanced capabilities can be flagged to move back to the free tier. Unlike ‘use it or lose it’, which can bring a novice user’s AI journey to an end with a bump, this isn’t a one-way street. All they need to do is work through the masterclasses and when they’re ready, they can be upgraded back to the paid tier.
We hope that balancing these two groups can increase your ROI from the licenses you’re paying for, without increasing spend, in a way that’s fair, easy to explain and easy to administer:
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