Data & AI
Strategies for enabling transformational value with data, analytics, and artificial intelligence
The Generative AI Revolution:
9 Trends Reshaping Healthcare in 2025
Gen AI in healthcare has brought much experimentation yet little transformation. As we move into 2025, we anticipate a pivotal shift where Gen AI will usher in the era of the “AI-Powered Clinician.” The organizations fully embracing Gen AI will achieve improved patient outcomes, step change clinician productivity and financial performance gains.
Our new report examines the current state of AI adoption and the opportunities leading healthcare organizations will seize over the next 12-24 months.
Impactful AI Podcast
This podcast from Impact Advisors’ Data and AI team explores how artificial intelligence (AI) is shaping the future of healthcare and beyond. Hosted by leaders of Impact Advisors’ AI practice, each episode features engaging conversations with AI models themselves, offering unique insights into how AI can improve lives and reduce burdens across the industry.
Challenges
The most common challenge among healthcare organizations is the lack of a clear enterprise-wide data and AI strategy, goals, or actionable roadmap. Without a clear vision of what you want to achieve, data and AI often becomes an assortment of expensive, disjointed reporting tools with little chance of providing meaningful insights or value.
Common challenges cited by healthcare organizations include:
- Data distrust or lack of agreement on common definitions, e.g., length of stay
- Multiple, costly analytics applications that are not delivering ROI
- Analytics stakeholders work in silos or are not well-aligned across the organization
- Lack of resources, skills, or focus limits ability to execute on critical projects in a timeline manner
- Data governance is not mature and may be cumbersome or non-existent
Value Delivered
How We Deliver Value
Impact Advisors helps you envision the big picture of data, enterprise analytics, and AI, develop a plan that considers where you are today and what can reasonably be achieved over the near and long-term, and then supports your team with tools, resources, and expertise at every step of your journey.
Our data and AI professionals average 20 years of experience in roles ranging from executive-level strategic analytics to program leadership to technical engineering and development of data products across a variety of industries. Their expertise ranges from highly relevant technical skills (e.g., Epic Analytics Suite, Healthy Planet, Tableau, Power BI, Oracle, SQL, Azure, IBM, Hadoop, etc.) and strategic skills, such as SDOH, Data Governance, and Program Management.
Data Strategy & AI Transformation
Assessment and Planning for Analytics Performance: Conducting thorough evaluations to identify current capabilities and areas for improvement in analytics performance.
Analytics Strategy for Mergers and Acquisitions: Developing strategic plans to integrate and leverage analytics during corporate restructuring or business expansion.
Evaluating AI System Effectiveness: Measuring the performance and impact of AI systems to ensure they meet desired outcomes and provide value.
Structuring an Analytics Team with Industry Practices: Building an analytics team based on best practices within the industry to optimize collaboration and efficiency.
Data & Tech Optimization
Assessing, Designing, and Implementing Value Targeted Analytics Solutions: Evaluating business needs to design and implement analytics solutions that deliver targeted value.
Moving Analytics to Cloud Platforms (Epic Nebula, Azure, Snowflake): Transitioning analytics operations to cloud platforms for enhanced scalability, performance, and cost-effectiveness.
Expertise in Data Visualization and Data Architecture: Demonstrating advanced skills in presenting data visually and structuring data architecture to support analytics insights.
Agile Development and Coaching for Analytics Products: Employing agile methodologies in the development of analytics products and providing coaching to ensure agile practices.
Data Operations
Data Asset Discovery & Analysis: Identifying and cataloging key data assets and prioritizing those most valuable to your organization.
Implementing Analytics ROI Measurement: Establishing metrics and processes to calculate the return on investment for analytics initiatives and enable effective decision-making.
Consolidating Analytics Tools and Data Migration: Streamlining analytics tools and processes, and managing the migration of data to new systems.
Comprehensive Analytics Services with Specialized Staff Augmentation: Offering a full suite of analytics services, supplemented by specialized staff to address specific needs.
Our Leaders
Liam Bouchier – Data & AI Practice Lead
Liam’s 15-year career has been largely focused on enterprise-scale data systems transformation in both the private and public sectors, with well over a decade focused on healthcare data systems across care transformation, population health, research, “big data” technologies, and EMR data ecosystems. More recently, he has been helping clients navigate emerging AI technologies and their real-world application in healthcare to improve patient outcomes, improve quality and lower cost.
AI/Artificial Intelligence
AI/Artificial Intelligence
AI/Artificial Intelligence
Ready to join the team?
Start making
your impact today!
If you are passionate about improving healthcare, we’d like to know you. Check out our current list of openings or talk to one of our recruiters.
