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Multiverse Enrolls NHS and Council Workers in Taxpayer-Funded AI and Data Courses

Multiverse, an apprenticeship company founded by Euan Blair, has enrolled workers from the NHS and councils in AI and data training programs funded by the government's apprenticeship levy. Examples include podiatrists, pharmacists, funeral plan consultants, and security guards. The company states that role fit criteria are applied during onboarding, while completion rates for its programs were jus

The Times
1 source·Apr 13, 8:18 PM(2 hrs ago)·2m read
Multiverse Enrolls NHS and Council Workers in Taxpayer-Funded AI and Data CoursesThe Times
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Multiverse, an apprenticeship company founded by Euan Blair, provides training programs funded through the government's apprenticeship levy. 5 percent of their wage bill to a training pot, with unspent funds returned to the Treasury. These programs support workers in various sectors, including the NHS and local councils, with training costs up to £18,000 per person.

4 billion, has expanded rapidly since its founding. It has enrolled employees in data and artificial intelligence courses. Specific examples include an NHS podiatry team leader and a lead pharmacist in cancer services undertaking data-focused programs, as well as a council community protection officer enrolled in an AI course.

Other enrollees include a funeral plan consultant, a secondary school teacher, and a parking enforcement CCTV manager studying for data or AI qualifications. These cases span NHS trusts, councils, schools, and employers such as John Lewis and Arriva. Roles involved range from clinicians and teachers to council officers, warehouse staff, and administrative workers.

Enrollment and Suitability Processes Internal material indicates that about 60 percent of learners completed an assessment of whether their role fit the qualification.

Multiverse stated that role fit criteria are applied as part of the onboarding process for all programs. The company published research showing that its AI and data learners hold a range of job titles. In one instance, a nurse raised concerns after being placed on a highly technical qualification.

A funeral plan consultant, Rebecca Mahony, did not complete a data apprenticeship, stating it was not relevant to her role and that her workload prevented participation. Apprenticeships require employees to spend a proportion of working hours on training, which can affect core duties.

Completion Rates and Growth Official data show that just over half of Multiverse learners completed their courses in 2024-25, with some programs closer to 40 percent.

The company uses a 42-day qualifying period, set by the Department for Education, during which early leavers are not counted in performance data. Multiverse described this as a probationary window. A former senior member of the sales team reported pressure to increase enrollment in line with the company's growth.

The firm has not made a profit despite its expansion. Senior NHS figures noted receipt of legal correspondence from Multiverse after questions about its programs.

Contract and Legal Interactions An NHS trust received a legal letter after introducing criteria, including completion rates, that affected Multiverse's eligibility.

A proposed contract worth tens of millions of pounds was halted due to concerns about the tender process. When the trust later conducted a competitive process, Multiverse did not meet key requirements. Multiverse denied threatening NHS figures or trusts, stating any legal action was directed at a third party rather than NHS organizations.

The interactions highlight ongoing discussions about program suitability and funding use in public sector training.

Story Timeline

3 events
  1. 2024-25

    Just over half of Multiverse learners completed their courses according to official data.

    1 sourceThe Times
  2. Recent years

    Multiverse expanded rapidly and reached a valuation of £1.4 billion without profitability.

    1 sourceThe Times
  3. April 13, 2026

    Reports emerged of criticism over enrolling NHS and council workers in AI courses.

    1 sourceThe Times

Potential Impact

  1. 01

    NHS trusts could revise contracts with training providers based on completion concerns.

  2. 02

    Scrutiny may lead to stricter role fit assessments in apprenticeship programs.

  3. 03

    Taxpayer-funded training allocation might shift to more suitable programs.

  4. 04

    Legal disputes with public sector entities may increase for similar firms.

Multi-source corroboration verifies facts, not framing. This panel scores the Substrate rewrite you just read (top score) and the raw source bundle it came from. A positive delta means the rewrite stripped framing from the sources; a negative or zero delta means our neutralizer let some through.

Sources vs rewrite
Sources
55/100
Rewrite
42/100
Delta
13
Source framing: The article frames Multiverse's apprenticeship push as aggressive and unsuitable through insider claims and negative examples, emphasizing criticism over the company's growth and potential benefits.
Interventions:signal-correction retry
How else this could be read

Multiverse's innovative AI training equips public sector workers with future-proof skills, boosting employability despite rapid scaling challenges.

Signals detected
  • Valence skewnotable
    nurse raised concerns after being placed on a highly technical qualification
    Negative adjectives and verbs skew toward program mismatchAdjectives and adverbs systematically slant toward one interpretation even though the underlying facts are neutral.
  • Omitted counterpointnotable
    No mention of successful outcomes or benefits from programs
    Ignores potential positive impacts on public sector skillsA reasonable alternative reading of the facts isn't represented anywhere in the source bundle.
  • Selective sourcingminor
    Senior NHS figures noted receipt of legal correspondence
    Critics' views prominent without balancing company defenseEvery quoted expert shares one viewpoint; no counter-expert is given meaningful space.
Source ideological mix
Left 0Center 0Right 1
1 source classified — lean diversity reduces framing-consensus risk.

Transparency Panel

Sources cross-referenced1
Framing risk42/100 (moderate)
Confidence score65%
Synthesized bySubstrate AI (grok-4-fast-non-reasoning)
Word count464 words
PublishedApr 13, 2026, 8:18 PM
Bias signals removed3 across 2 outlets
Signal Breakdown
Loaded 1Editorializing 1Amplifying 1

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