The Master of Science in Artificial Intelligence (MSAI) degree is an emerging graduate degree program that is taking center stage in the fields of artificial intelligence, business intelligence, and data analytics. This skills-based, interdisciplinary degree program emphasizes applied learning, allowing graduates to advance their careers and pursue leadership positions in these evolving fields.
Whether you are considering a career change to data analytics or looking to pursue high-level machine learning engineer roles, you will find that the MSAI degree opens the doors to a wide range of career possibilities.
The Master of Science in Artificial Intelligence (MSAI) is an interdisciplinary degree program that goes beyond skill-building. It integrates artificial intelligence fluency, advanced data analysis expertise, and essential business acumen, specifically preparing graduates for advanced leadership roles.
These are some of the core competencies that this graduate degree focuses on, and how they can be applied in business intelligence careers:
This advanced graduate degree program prepares you for role families, allowing you to understand career progression within your chosen field. Common role families you'll see in job listings may include IT and data engineering families.
The following contains some of the career paths that MSAI graduates can explore:
An analytics manager is a data scientist who leads a team of data analysts for an organization. They often gather AI data analytics ideas and work to create a comprehensive strategy for the data analysts to enact. According to the Bureau of Labor Statistics (BLS), the analytics manager salary can see wages of about $112,000, and the average analytics manager's salary may be comparable.
The number of AI product manager certification jobs is on the rise, as organizations look to bridge the gap between AI technology and AI-powered products. AI product managers work to develop practical AI products in demand with consumers. Professionals interested in this career path may want to consider an AI product management certification program to specialize in this field.
The growing number of data strategist jobs highlights the demand for business intelligence professionals who have an advanced understanding of AI technology. Data strategists work to create evidence-based plans for organizations, highlighting how they can better use data to achieve long-term and short-term goals. In addition to AI fluency and data analysis skills, data strategists and analytics translators should have well-developed executive presentation skills.
Additional pathways that MSAI graduates may want to explore include:
Whether you are most interested in remote data analytics jobs or you are looking to make an impact in-person, these are the sectors that are often looking for MSAI graduates:
The healthcare field is becoming increasingly dependent on advanced technology. AI-powered products are streamlining operations and improving the precision of personalized patient care.
Within the financial services and insurance sectors, business intelligence and data analyst professionals are in high demand, as these industries look to leverage the power of data to identify emerging trends, reduce risk, and improve operational strategy.
Data analysts and AI professionals in the retail and consumer packaged goods sectors work to extract insights to create products that align with market demands. There is expected to be an increasing number of AI product manager jobs in the coming years within these sectors.
Within the SaaS and technology sectors, data analysts work to transform raw data into actionable insights for organizations. Graduates will find many product analytics jobs in these sectors.
Even within the public sector, there is demand for AI business analysts and data professionals. In most cases, these professionals use a data strategy to improve decision-making within the organization.
Choosing the right MSAI program requires you to evaluate the required coursework and determine whether it will prepare you for the data strategist jobs that you are most interested in.
It's important to select a program that is designed for career advancement. The assignments that you complete should enable you to work with advanced business intelligence tools and develop the core competencies required to bridge the gap between data science and business development.
Capstone projects allow you to apply your learning in real-world environments, giving you actionable skills that can drive career growth. The best AI capstone project ideas should showcase your use of advanced techniques, such as natural language processing or machine learning technology, to solve real-world problems.
Recruiters seeking top talent in artificial intelligence and data analytics are looking for resumes that showcase a candidate's knowledge beyond the data engineering basics. They want to identify candidates who know how to apply their skills in real-time and who know how to navigate the global markets.
Your portfolio should showcase these in-demand artifacts:
Metrics and outcomes to stand out to AI talent recruiters include:
LinkedIn continues to be a powerful platform for professionals interested in career advancement. After graduating from an MSAI program, you will want to use the top LinkedIn strategies to improve your visibility online:
Your LinkedIn headline counts, use powerful keywords and actionable messaging within your headline. Enhance the top portion of your profile with a summary that includes action verbs and quantifiable results.
Build out your LinkedIn profile by incorporating professional experiences and capstone projects, showcasing your ability to apply your AI fluency in practical environments.
In reality, most recruiters will only spend a few brief moments scanning your resume to determine if you are a good fit. You need to use the 6-second scan challenge to capture their attention and maximize your impact.
Your resume should only be one page, regardless of your professional experience and background. Keep the most high-impact experience at the top.
Avoid bogging your resume down with industry jargon. Instead, highlight measurable results and quantifiable outcomes, showcasing how you can have an impact on any organization.
In addition to preparing your resume, you will want to hone your interview skills so that you can successfully present your qualifications and experiences in person.
Build your story bank by identifying key experiences that shaped you as a professional. Your story bank should include anecdotal examples of times that you solved complex problems, improved precision within an organization, or took on a leadership role.
Interviewers may use case patterns to learn more about how candidates resolve business problems. When using case patterns, interviewers are looking for candidates who can think creatively, develop a structured approach to problem-solving, and apply analytical skills in real-time.
When comparing data science vs. analytics roles, you may need to adapt accordingly depending on where you are in your career. Graduates in the early stages of their careers will position their MSAI degree differently than those at the height of their careers.
If you are considering a career change to data analytics, or you are pursuing your first professional opportunity, you will want to showcase your MSAI degree in a way that highlights your commitment to advanced education and skill development.
In the middle of your career, you will want to position your MSAI degree as a platform for building leadership skills so you can take on more advanced roles in the field.
A 30- to 60-day visibility plan provides you with a structured roadmap for improving your reach within the job market, allowing you to access the best available jobs.
This is what a 30- to 60-day visibility plan can look like:
In the first two weeks, you should begin drafting a template and defining your career goals. Be sure to identify the metrics that you will use to track your progress.
Within the next few weeks, begin learning more about employers' expectations, and refine your resume accordingly. Position yourself so that you are highly visible online and within your local professional network.
In the final weeks, work to apply your newfound skills in practical ways, allowing you to build a resume that highlights powerful artifacts, such as a case study or a decision memo example.
Navigating an evolving job market can be tricky, particularly in the AI era, when technology is rapidly changing to meet the needs of organizations and consumers.
These are some of the common mistakes that MSAI graduates make, and how you can avoid them during your job search:
Graduates are often excited and proud of their actionable, transferable AI skills — but creating a portfolio that highlights skills without showcasing business context will leave employers wondering what they should do with those skills. You must show how your AI fluency can be applied in practical business settings.
Listing the AI tools that you have proficiency with is great, but you need to explain what impact those tools can have within an organization.
Try to avoid highlighting the most complex and impressive models that you have created, unless you can prove that this model offers effective and efficient results. The key is to showcase the practical application of your knowledge and skills.
Match your energy to the work. Analytics managers run experiments and metrics, AI product managers ship features and coordinate builders, and data strategists turn executive goals into roadmaps. Pilot tasks in each lane before choosing.
Translate the problem structure and KPI to the new domain. Show the decision you changed, the metric movement, and what you would adapt for the target sector.
Enough depth to show you can deliver. Highlight your core stack, such as SQL, Python, DBT, Airflow, Power BI, or Tableau, and include up to 3 shipped outcomes. Save complex architecture details for your portfolio.
The best artifacts to include on LinkedIn include short demo videos, a decision memo example, evaluation dashboards, and before-and-after snapshots.
Without direct leadership experience, you can highlight cross-functional wins, such as times when you drove a pilot, aligned stakeholders, created a runbook, or mentored peers.
Yes, if they’re relevant to your target role. Pair each certification with a shipped artifact to avoid appearing as if you have classroom-only experience.
Without A/B testing experience, you can show structured alternatives, such as pre- or post with holdouts, matched cohorts, or pilot regions. Be transparent about limitations and triangulate with adoption plus qualitative feedback.
If you are looking to position yourself as a leader in the midst of the digital transformation, then an online AI degree is the right investment. The Master of Science in Artificial Intelligence (MSAI) with a specialization in Data Analytics is an interdisciplinary, applied graduate degree program at Indiana Wesleyan University that is designed for experienced professionals who want to advance their careers. The curriculum for this program equips students with the practical knowledge and technical experience required to solve complex organizational problems using machine learning, natural language processing, and predictive analytics.
Learn more about our degree programs, request more information about our MSAI degree, and apply to IWU today.
