Advice for the
decisions that matter.
Independent advice on where to invest in AI, how to manage its risks, and what your organization needs to succeed.
Explore our expertise
Start with the question your organization needs to answer.
Enterprise AI strategy
Set priorities, evaluate technologies, and develop direction with on-demand executive advice.
Explore enterprise ai strategy →AI governance & risk
Explore responsibility, oversight, ethics, and the evidence needed to govern AI.
Explore ai governance & risk →AI due diligence
Investigate the technology behind investment claims and transaction decisions.
Explore ai due diligence →Automation & change
Connect automation choices to workflows, organizational change, and skills.
Explore automation & change →Advice shaped around
your responsibilities.
Enterprise leaders
Boards, C-suite leaders, technology executives, and business teams considering AI adoption and oversight.
Investors and deal teams
Private equity, venture capital, investment banks, and enterprise M&A teams examining technology and data assets.
Institutions and professional communities
Public-sector organizations, professional associations, and learning teams developing their understanding of AI.
Start with the decision
you need to make.
The work can begin with an executive briefing, a research question, or a specific business challenge. We shape the advice around your situation.
We agree what you need to understand, who will use the advice, and what the work should deliver.
Questions about AI advisory.
When is independent AI advice useful?
Independent analysis helps when a technology decision has significant business consequences. RPA2AI’s work includes assessing technology choices, shaping adoption plans and examining investments.
Advice is especially useful when a proposal combines attractive capabilities with unfamiliar risks. Separate questions about what the system can do from questions about its permitted use and the consequences of failure. Kashyap’s responsible-strategy article provides a starting point for bringing these considerations into the same decision. Read more about responsible AI strategy.
Should an AI strategy begin with a vendor shortlist?
Begin with requirements and the business context. RPA2AI’s technology selection work evaluates products and implementation partners against the organization’s needs.
Use a shortlist to test a set of requirements, rather than allowing the available demonstrations to define the problem. Compare performance under realistic conditions, integration requirements and operating constraints. Kashyap’s enterprise evaluation article describes how to assess these factors alongside technical capability. Read more about enterprise AI evaluation.
What should an AI investment review cover beyond the model?
Review data rights, technical capability and competitive differentiation alongside the investment case. Model performance is one part of assessing whether a business can deliver on its claims.
Ask whether the evidence covers the system’s intended use, data provenance and deployment practices. An assessment that ends at a performance score leaves important business exposure unexplored. Kashyap’s article on AI audits explains how a broader examination can support diligence and identify issues requiring action. Read more about auditing AI systems.
How can governance support AI adoption?
Clear ownership makes decisions and corrections possible. Governance should establish who is accountable for outcomes and how problems are detected, escalated and addressed.
Governance should connect ethical objectives to the way decisions are made and checked. Teams need a shared understanding of the outcomes they want to protect, as well as practical measures for doing so. Kashyap’s comparison of ethical and responsible AI explains why principles and implementation depend on each other. Read more about ethical and responsible AI.
Can RPA2AI help a leadership team understand AI before making a commitment?
Yes. Research and education are part of RPA2AI’s published offering. A briefing can establish a shared understanding of the technology and the decisions ahead.
What is your next AI decision?
Talk to us about your business priorities, an investment, or your team’s learning needs.