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Unlocking the power of data at your firm could start with building prototypes and dashboards, but it shouldn’t end there. Becoming a true data-driven organization means upskilling your leaders and your entire workforce with the latest data training, analytics, and artificial intelligence (AI) training.
AI training built to scale adoption across the organization
AI changes how decisions get made, how work flows, and where value is created. Real impact rarely comes from a single course. It comes from shared understanding, clear priorities, and adoption in day-to-day work — at scale, across teams and roles.
At DAIN Studios, we design and deliver training based on real transformation work, from Data & AI strategy to operating models to implementation. Our training is industry-agnostic and technology-agnostic. We focus on what AI changes in the way your organization works, and how you adopt it safely and effectively — using the tools and environments you already operate in.
Tell us who you’re training and what you need to scale. We’ll recommend the fastest path to organization-wide adoption.
Learn Agentic AI with Harvard and DAIN Studios
Together with the Harvard Data Science Initiative and Next Gen Learning, DAIN Studios co-designs and teaches the Agentic AI Intensive, a 2.5-week online program for executives and business leaders. The course focuses on moving from AI pilots to agent-first workflows using our A.G.E.N.T. Framework, real industry cases and an AI tutor that adapts to each participant. If you want to deepen your own capabilities, you can apply to join one of the upcoming cohorts.
Choose your starting point
Different starting points, same goal: scalable AI use across the organization.
Align executive direction and sponsorship
For: Executive teams, management teams, BU heads Typical time investment: 1–2 hours, ½–1 day, or a multi-session program Outcome: Leaders align on what AI changes, what to prioritise, and how to sponsor adoption at scale.
Activate AI champions to make adoption stick
For: Team leads, unit leads, transformation leads, selected experts Typical time investment: 3–6 months (mixed cadence) Outcome: Champions create repeatable ways of working and scale adoption across teams.
Raise AI literacy at scale across roles and locations
For: Knowledge workers, experts, and frontline roles
Typical time investment: Modular e-learning program (short video lessons and exercises) plus rollout and engagement support
Outcome: A shared baseline for practical, responsible AI use that scales across roles and locations.
What gets built during training
Most programs include a practical build component tied to real work — so adoption spreads beyond the training room.
Role-specific AI assistants for real tasks (e.g., custom GPTs / internal copilots)
Reusable workflow patterns and templates teams can apply immediately
Prioritised use-case backlog with owners and next steps
Safe-use practices (do/don’t, escalation paths, governance basics)
Rollout and measurement signals to track adoption and improve continuously
Executive direction and sponsorship
Who it’s for:
Executive teams, management teams and BU heads (and sometimes the board) who need a shared, realistic understanding of AI and decisions they can act on — to steer adoption across the organization.
Typical situations
- AI is clearly relevant, but leaders lack hands-on intuition and a common language for what is possible.
- Competitors are moving faster, but priorities are unclear and pilots are scattered.
- You want to use existing assets (data, processes, customer touchpoints) more deliberately and identify where AI creates measurable advantage.
Business outcomes
- Shared, realistic understanding of AI (opportunities and limits)
- Clear priorities (what to do now, what to do later)
- Better sponsorship of adoption (leaders know what to ask for and how to enable)
- Stronger decisions on data and AI investments (fewer random pilots)
- A practical stance on risk and governance that enables progress
Recommended formats
- Keynote / briefing (1–2 hours)
A focused update and alignment session with clear implications for your organization.
- Leadership summit (½ day to 1 week)
Deeper working sessions with leadership, tailored to your context and priorities.
- Learning journey (10 sessions over ~3 months)
A structured series that builds understanding, governance stance, prioritisation, and sponsorship behaviours over time.
- Ongoing executive support and mentoring (weekly or monthly)
Lightweight steering support while adoption and implementation is underway.
Practical build component (examples)
- A decision frame leaders can use to fund / stop / scale initiatives
- A first-wave shortlist of workflows or use cases to transform
- Optional hands-on prototyping of role-specific assistants (e.g., custom GPTs) to build intuition
What you get (deliverables)
- Executive-ready principles for AI use and adoption
- A prioritised opportunity or use-case shortlist
- A lightweight roadmap (next 90 days / 6 months)
- A decision frame: what to fund, what to stop, what to scale
- Optional input into AI strategy and operating model work
- Optional hands-on exercises that build intuition (without turning it into tool certification)
Case snapshot: Leadership summit
Industry: Media & Publishing organization (global leadership group) Audience/Scale: ~100 leaders across multiple domains Format: Leadership summit with hands-on ideation and rapid prototyping using guided assistants (e.g., custom GPTs) Outcome: Leaders developed 13 strategic AI concepts with working prototypes; several were selected for development and leaders initiated local workflow evaluations with their teams.Activate AI champions to make adoption stick
Who it’s for:
Team leads, unit leads, transformation leads, and selected high-impact experts expected to drive change across the organization — especially in larger companies with heterogeneous roles and uneven maturity.
Typical situations
- You have momentum, but adoption is uneven and teams move at different speeds.
- Governance, security, and ways of working create friction or uncertainty in day-to-day use.
- Skills are imbalanced. Pockets of expertise exist, but the organization lacks internal “force multipliers”.
Business outcomes
- AI maturity increases across functions through practical, repeatable ways of working
- New methods and efficiency improvements show up in day-to-day work (not only pilots)
- Increased readiness for AI-driven transformation
- A measurable approach to adoption and continuous improvement
Recommended format
Champions program (3–6 months, mixed cadence)
A structured program combining:
- AI fundamentals refresh (shared baseline)
- Governance and safe ways of working (clear do/don’t, escalation paths)
- Use-case discovery and prioritisation (value and feasibility)
- Measurement (adoption signals and feedback loops)
- Enablement layer: train-the-trainer methods and internal rollout support
Scale guidance:
Cohort size depends on organization size and the scope of change. As an example, in a ~1,000-person organization the champions group can be ~20 people (or more) with a mandate to drive initiatives across domains.
Practical build component (examples)
- Champions create and test repeatable workshop formats (train-the-trainer)
- Teams build a first workflow library and assistant patterns for internal reuse
- A concrete rollout plan + adoption signals are defined and owned
What you get (deliverables)
- Shared ways of working for AI (safe use, escalation, governance basics)
- A prioritised use-case backlog with owners
- A lightweight measurement model (adoption signals and cadence)
- A champions playbook (how to support teams and spread practices)
- A reusable workflow library (patterns and templates)
- Community setup (channel, rituals, office hours)
- Internal comms assets (FAQs, launch messages, participation guidance)
- A “next 90 days” rollout plan to activate the organization
Case snapshot: Champions train-the-trainer rollout
Industry: Retail & Payment Services organization Audience/Scale: ~15 selected experts with mandate across multiple domains Format: 10-week train-the-trainer program (self-study + intensive workshop + facilitated rollout) Outcome: Ambassadors gained a facilitator toolkit and prioritisation method to run use-case workshops independently, creating a multiplier effect for sustainable adoption.Raise AI literacy at scale across roles and teams
Who it’s for:
Organizations that want a shared baseline across knowledge work and frontline roles, including experts, knowledge workers, and operational staff such as factory operators.
Typical situations
- Upskilling is recognised as necessary, but the organization lacks a scalable approach.
- Efficiency in day-to-day work is under pressure, and teams need practical support.
- Skill levels vary widely across roles, locations, and teams, creating uneven adoption and avoidable risk.
Business outcomes
- Baseline AI literacy across roles (common language and confidence)
- Responsible use (policy-aware behaviour, AI Act literacy where relevant)
- Productivity improvements in recurring work (time saved on drafting, summarising, searching, reporting)
- Better use-case identification from employees (stronger pipeline)
- Faster adoption of GenAI tools already available internally
- Reduced risk incidents through shared ways of working and policy-aware behaviour
- More cross-team collaboration through a shared baseline and common practices
- Better visibility for management (completion, engagement, feedback)
Recommended formats
- Modular e-learning for AI literacy
A structured series of short lessons that moves from AI basics and responsible use to role-based scenarios and your organization’s context.
- Global use-case ideation session (remote, large audience)
A structured format to source ideas across time zones and roles.
- Community layer
Office hours, sharing rituals and internal prompts to sustain momentum.
- Measurement and reporting (optional but recommended for scale)
Participation, completion, feedback and follow-up signals to guide improvements.
Practical build component (examples)
- Teams apply learnings to real tasks via guided exercises (e.g., drafting, summarising, reporting)
- Optional creation of role-specific assistants (e.g., custom GPTs/internal copilots) using approved sources and safe-use patterns
- Outputs feed into a structured opportunity pipeline (use-case backlog)
What you get (deliverables)
- AI literacy modules: a series of short video lessons with exercises and quizzes, covering fundamentals, safe ways of working, and client-context examples
- High-quality videos, exercises and short knowledge checks
- Launch and comms plan (multi-channel rollout)
- Engagement plan (nudges, participation tactics, retention)
- KPIs and tracking (completion, engagement, feedback)
- Optional community setup (channel, prompts, rituals)
- Optional live sessions (Q&A / office hours)
- Summary pack: “what to do next” recommendations after the baseline
Case snapshot: AI literacy at scale
Industry: Nordic flag carrier Audience/Scale: Up to ~1,000 employees trained Format: Modular e-learning program + rollout support Outcome: Established a shared baseline for practical AI use across roles and locations.Case snapshot: AI literacy + compliance baseline
Industry: Renewable materials manufacturing organization Audience/Scale: Organization-wide rollout (multiple roles and locations) Format: Self-paced e-learning (4 modules / 18 lessons / 90–100 minutes total) Outcome: Built AI literacy and AI Act awareness at scale, enabling employees to identify AI opportunities in daily work.Case snapshot: Hands-on literacy for operational change
Industry: Global pharmaceutical organization Audience/Scale: Cross-role groups from frontline to leadership Format: In-person literacy workshops with hands-on exercises Outcome: Improved cross-role collaboration and readiness for data/AI-driven ways of working during a major operational ramp-up.Case Study: Unlocking Value Through AI at Linde
A global program to raise GenAI literacy and generate use cases at scale across time zones, moving from awareness to validated opportunities and implementation.
Highlights (from the case):
- 500+ participants across 7 time zones in the intro phase
- 300+ contributors in use-case ideation
- 70+ initial use cases narrowed to 10 validated NLP use cases
- One implemented solution reduced report generation time from 24 hours to 2 hours, saving thousands of hours annually and several million euros per year (as described in the case)
Learning is a capability, not an event
Training works best when it supports adoption over time and connects to how work is done. Scaling AI use typically requires three things working together:
- Executive direction builds prioritisation and sponsorship
- Champions create repeatable ways of working
- Workforce baseline creates shared language and safe daily use
Most organizations start with one entry point and expand as momentum grows. Tell us where you want to start — executive direction, champions, or workforce baseline — and what you need to scale. We’ll recommend the right format and a practical build component. Contact us to discuss training.
Tell us who you want to train and choose the best starting point. We’ll help you refine it and recommend a format — including a practical build component that supports adoption at scale.