Building Your AI Adoption Roadmap
Most AI roadmaps are either a strategy deck with no sequence or a project list with no logic. This course teaches the thing in between: a one-page, twelve-month roadmap that says which use cases, in what order, with what enabling work, measured how. You'll learn to find use cases in the work, score and balance them, sequence them in waves, and say no with a reason and a date. You'll finish with a draft roadmap and a plan for running its first quarterly review.
Course details
Duration
1h 12m 24s
Lectures
15
Video
1.25 hours
Quizzes
1
Level
Beginner
Course Description
A roadmap turns AI ambition into an order of operations. This course builds one page your organization can run: the outcome and appetite at the top, three waves of use cases, the enabling work beside them, and the parked list with review dates at the bottom.
What you'll learn
- The difference between a strategy, a roadmap, and a project list, and the roadmap's four jobs
- Finding use cases from process pain, volume, bottlenecks, and customer friction
- Scoring value, feasibility, risk, and readiness, and balancing the portfolio
- Sequencing in prove, scale, and transform waves with data, tools, skills, and governance one wave ahead
- Pilot charters with scale and kill criteria, resourcing, risk tiers, and an incidents plan
- Baselines, the quarterly review, communicating at three altitudes, and adjusting by the rules
Who it's for
Executives, AI leads, transformation and strategy teams, and department heads who plan and run AI adoption.
15 short video lessons in three modules: From Ambition to Use Cases; Sequencing and Enablement; and Running the Roadmap.
This course is educational and is not legal or financial advice. Your organization's AI policy governs.
Module 1: From Ambition to Use Cases
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1.1 What a Roadmap Is ForThe difference between a strategy, a roadmap, and a project list — the roadmap as a sequencing and communication tool.
In this lesson:
- Distinguish a strategy, a roadmap, and a project list
- State what a roadmap has to do for the organization
- Adopt the one-page roadmap format used in this course
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1.2 Finding Use Cases Where the Work Actually Is
Process pain, repetitive volume, decision bottlenecks, customer friction — sourcing from the floor, not the vendor deck.
In this lesson:
- Source AI use cases from the work rather than from vendor demos
- Apply the four signals that mark a strong use case
- Run a use-case discovery that produces a usable inventory
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1.3 Scoring: Value, Feasibility, Risk, Readiness
The four-factor score, applied consistently — why "easy and valuable" beats "impressive."
In this lesson:
- Score use cases on value, feasibility, risk, and readiness with a consistent rubric
- Rank an inventory so the order can be defended
- Resist the pull of impressive over easy-and-valuable
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1.4 The Portfolio View
Quick wins, capability builders, strategic bets — balancing horizons and appetite.
In this lesson:
- Classify use cases into quick wins, capability builders, and strategic bets
- Balance the roadmap across horizons and risk appetite
- Spot a portfolio that is all one kind
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1.5 Saying No: What Not to Do This Year
The parked list, the reasons, and the review date.
In this lesson:
- Build a parked list that holds
- Give each parked item a reason and a review date
- Handle the pressure to un-park
Module 2: Sequencing and Enablement
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2.1 Waves, Not Big Bangs
Wave one proves, wave two scales, wave three transforms — what each wave needs to have in place.
In this lesson:
- Explain why AI adoption is sequenced in waves
- Define what each of the three waves is for
- Set the entry conditions for each wave
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2.2 Dependencies: Data, Tools, Skills, Governance
The enabling workstreams that run beside the use cases — the sequencing constraints they impose.
In this lesson:
- Define the four enabling workstreams on a roadmap
- Draw the dependencies between enabling work and use cases
- Sequence enabling work one wave ahead of what needs it
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2.3 Pilots That Are Designed to Scale
Success criteria, the scale decision written before the pilot starts — and the kill criteria too.
In this lesson:
- Design a pilot whose result leads to a decision
- Write the scale and kill criteria before the pilot starts
- Run the pilot as a rehearsal for scale, not a demo
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2.4 Resourcing the Roadmap
Teams, time, budget, and the champions network — what leaders protect and what they let go.
In this lesson:
- Size the people, time, and budget a roadmap actually needs
- Build a champions network that carries adoption
- Decide what leaders protect and what they let go to make room
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2.5 Risks and Guardrails on the Roadmap
The risk tier of each use case, the review gates, and the incidents plan.
In this lesson:
- Assign a risk tier to every use case on the roadmap
- Place review gates where the tiers require them
- Write the incidents plan the roadmap carries
Module 3: Running the Roadmap
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3.1 Success Metrics Defined Before Launch
Leading and lagging indicators per use case, baseline measurement, and who reports.
In this lesson:
- Define leading and lagging metrics for each use case before launch
- Take a baseline the results can be compared against
- Assign who reports what, and how often
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3.2 The Quarterly Roadmap Review
What changed, what to accelerate, what to stop — the portfolio decisions and how to make them fast.
In this lesson:
- Run a quarterly review that produces decisions
- Use the five questions that structure it
- Make continue, accelerate, and stop decisions quickly and in writing
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3.3 Communicating the Roadmap
The one-page version for the board, the team version, the all-hands version — the same roadmap, three altitudes.
In this lesson:
- Present the same roadmap at three altitudes without changing its substance
- Answer the question each audience is actually asking
- Keep the roadmap communication honest as it changes
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3.4 When the Roadmap Meets Reality
Vendor changes, model changes, a failed pilot, a regulatory shift — adjusting without abandoning.
In this lesson:
- Recognize the four shocks that hit every AI roadmap
- Adjust the roadmap by its own rules rather than abandoning it
- Tell the difference between a shock that changes the sequence and one that changes the strategy
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3.5 Your Twelve-Month Roadmap
The one-page draft assembled from the course — the checklist and your first quarterly review; the finale.
In this lesson:
- Assemble the one-page roadmap from the course's components
- Run the completeness checklist before publishing
- Complete Building Your AI Adoption Roadmap
Building Your AI Adoption Roadmap — Final Exam
Learn at your own pace
Study the materials at your convenience, you can always return to them to repeat
Certificate of completion
Complete every lesson and pass the final exam to earn a RiseCert certificate of completion you can download and share.
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Got Questions? We've Got Answers!
Answers to the most common questions about this course.
What is the Building Your AI Adoption Roadmap course?
Building Your AI Adoption Roadmap is a RiseCert online course that teaches leaders to build a one-page, twelve-month AI roadmap: which use cases, in what order, with what enabling work, measured how. It includes 15 video lessons (about 1 hour 15 minutes) and a final exam, and you finish with a draft roadmap of your own.
Who should take a course on building an AI adoption roadmap?
Executives, AI leads, transformation and strategy teams, operations leaders, and department heads who decide which AI use cases an organization pursues and in what order. Use-case owners, enablement leads, and risk partners who will run or review the roadmap also benefit, because the course covers pilots, resourcing, risk tiers, and the quarterly review.
What is an AI adoption roadmap?
In the course's terms, an AI roadmap is the document between a strategy and a project list. The strategy says why, reviewed yearly; the project list says what's happening now, reviewed weekly. The roadmap says in what order: which use cases, in which waves, with which enabling work, measured how, reviewed quarterly, all on one page.
How do you prioritize AI use cases?
The course scores every use case from one to five on four factors: value, feasibility, risk, and readiness. Risk is scored inverted, and feasibility and readiness act as gates, so a score of one on either parks the use case regardless of value. Ties go to readiness, and the scores are published with the roadmap.
Why should AI be rolled out in waves instead of all at once?
The course explains that a big-bang launch peaks the support load on day one, makes the first failure public and simultaneous with others, and discovers enabling work mid-launch. Waves of three to five use cases a quarter apart let wave one prove the process, wave two scale it, and wave three attempt the strategic bets.
How do you design an AI pilot that leads to a decision?
The course uses a pilot charter written before day one: the question the pilot answers, two or three measures with baselines, scale criteria, kill criteria, and who decides on what date. The pilot runs as a rehearsal with a typical team and real inputs, and ends in scale, adjust, or stop.
Do I need technical skills or prior AI experience?
No. The course is written for leaders and planners, not engineers, and involves no coding. It assumes you can see how work flows in your organization and can bring people together to make decisions. Familiarity with basic AI tools helps, but every roadmap concept is explained in plain language with worked examples.
What will I be able to do after completing the course?
You'll be able to run a use-case discovery, score and rank an inventory, balance a portfolio, write a parked list with reasons and review dates, sequence waves with enabling work one wave ahead, charter pilots, tier risks, set metrics and baselines, run a quarterly review, and communicate the roadmap to the board, managers, and staff.
How is this different from a general AI strategy course?
A strategy course focuses on where AI fits the business and what appetite to set. This course starts where strategy ends: it turns the outcome and appetite into a sequenced, owned, measured plan, then shows how to run it through quarterly reviews and adjust it when vendors, models, pilots, or regulations change.
Does the course recommend specific AI tools or vendors?
No. Building Your AI Adoption Roadmap is vendor-neutral and does not endorse any product. It treats tools as one of four enabling workstreams alongside data, skills, and governance, and teaches how to re-score use cases when a vendor changes pricing or a model update changes behavior.
How long does the course take to complete?
The course has about 1 hour 15 minutes of video across 15 lessons, plus a final exam. Lessons run about five minutes each and are organized into three modules: From Ambition to Use Cases; Sequencing and Enablement; and Running the Roadmap. Most learners finish in two or three sittings.
Is the course online and self-paced?
Yes. The course is 100% online and self-paced, and your access does not expire. You can start, pause, and resume at any time on a computer, tablet, or phone with a modern web browser. There's nothing to install.
Is there a final exam?
Yes. The course ends with a 30-question multiple-choice final exam covering all three modules. You need a score of 80% or higher (24 of 30) to pass, and you can retake the exam as many times as you need. Finish all 15 lessons and pass the exam to complete the course and earn your certificate.
Do I get a certificate of completion?
Yes. After you complete all 15 lessons and pass the final exam, you can download a RiseCert certificate of completion from your account. It is a course completion certificate, not a license, professional certification, or continuing education (CE) certificate.
Does the course qualify for continuing education credit?
No. Building Your AI Adoption Roadmap is not currently approved or accredited for continuing education (CE, CPE, or CEU) credit by any state, licensing body, or professional association. If you need credit hours, take a course approved by the relevant body. This course is designed for practical planning skills.
Is the course content up to date?
Yes. The course is built around durable methods rather than specific products or versions, so it stays useful as tools change: scoring, waves, enabling work, pilot charters, baselines, and quarterly reviews. A full lesson covers adjusting the roadmap when vendor pricing, models, pilot results, or regulations change.
Can I use the course to build a roadmap for my own organization?
Yes. Each lesson fills in part of the same one-page roadmap, and the final lesson assembles it with a six-point pre-publication checklist and a plan for the first quarterly review ninety days later. The examples come from insurance, logistics, and healthcare administration, but the method applies to any organization.
Is this course legal or financial advice?
No. The course is educational and is not legal, financial, or investment advice. It teaches a planning method for AI adoption, but it can't tell you what your organization should fund or how regulations apply to you. Your organization's AI policy, its risk and legal teams, and qualified advisors govern specific decisions.
How much does the course cost, and can I enroll my team?
The course costs $99 per learner as a one-time purchase, with no subscription or recurring fees. To enroll a leadership team, department, or organization, contact RiseCert through the Contact Us page at risecert.org.
What is the refund policy?
All sales are final and no refunds are issued, as stated in the RiseCert Terms of Use. Please review the course description, lesson list, and these FAQs before purchasing, and contact RiseCert with any questions first.