Innovation is the heart of everything we do and, in many instances, equally shapes both small and large companies DNA. Today, as the era of disruption and turbulence continues, innovation plays a critical role in ensuring that companies remain competitive and resilient. It is becoming increasingly evident that artificial intelligence (AI) and data analytics are key enablers in achieving growth, scale, and efficiency through innovation.

The adoption of AI is an integral part of both “value creation” and “value protection“.

Our goal is for you to focus your resources and attention on “value creation” and let us handle the “value protection”.

The protection of AI value begins with establishing trust with your customers. We take a distinctive approach to AI Governance and Risk Management to ensure customer confidence in AI as well as meeting stakeholders’ and legal requirements.

OUR ADAPTIVE.AI SERVICES ADDRESS

  • AI Strategy and Governance
  • AI Risk Management
  • Assessment of gaps and maturity of AI trust enablers spanning ethics, privacy, security and robustness
  • Post-market monitoring and compliance of AI models and outcomes

For AI to deliver transformative value, enterprises need to strategize the value capture, creation, deployment and monitoring of AI models in the business ecosystem in which they operate.

We partner with you from the start of

Forging the Vision and Defining AI Strategy – through – Delivering Outcomes

– and everything in between

to close highlighted key Market Gaps

1.

Forge the Vision, Define AI Strategy

Investors

  • New sources of revenue at reduced risk

Customers

  • Improved experiences
  • Faster delivery, Address unmet needs

Leadership & Employees

  • Faster time to market
  • Quality Data Collection & Insights
  • Enrichment & Sandbox Exploration

2.

Management of AI Assets, Risk Management, and Tactical Execution

Infrastructure Enablers

  • AI & Data capabilities
  • Technology stack

Organization

  • Partnerships & Ecosystem

Software Development Lifecycle

  • Data and AI models
  • Test, Evaluate & Report and Deploy

3.

Measures and Outcomes

New data-based revenue / Monetization – Outcomes

  • Personalization
  • Digital Sales and Marketing
  • Improved Outcomes (cross functional)

Ongoing Monitoring

  • Feedback Human-Machine Learning

Scale, Learn and Innovate

Forge The Vision, Define AI Strategy

As organizations increasingly integrate AI into their operations, it becomes critical to establish effective governance and quantify the business value generated by AI use cases. Mismanagement of AI risks and inadequate data governance can lead to significant negative consequences for businesses. To address these challenges, our consultancy offers a range of services designed to help organizations- For more information, please see ‘Our Approach’ section.

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Management of AI Assets, Risk Management and Tactical Execution

To realize the benefits of AI, you must manage risks well. We recognize that the value of AI is a function of risk and returns, and selection of a suitable Risk Framework is one of the hallmarks of AI adoption success story. A well-thought through framework is a blend of leading industry best practices in risk management couple with risk dimensions related to human-machine interactions. Through robust AI governance and multi-stakeholder feedback these risks are identified, categorized, and impact clearly understood. Ultimately, the value of AI depends on a clear, common understanding of its scope, nature, context, and purpose, as…

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Measures and Outcomes

Our services in post-market placement of AI are geared toward helping customers achieve: These compelling drivers and trends below contribute to future sustainability of value and trust in AI in productive environment: Organizations that actively manage ethical issues, risks related to bias, privacy, human safety, transparency and security are well-positioned to preserve and protect their AI benefits both monetizable and in forging human-machine alliance.

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According to a recent survey of Gartner, two major points stand out reflective of post-generative AI market

  • Through 2025, the lack of AI skills will continue to be the No. 1 challenge for enterprises looking to succeed in their AI initiatives.
  • By 2026, organizations that prioritize and operationalize AI transparency and trust will see their AI models achieve improved results in terms of adoption, business goals and user acceptance

Deep Expertise – Data & Risk | Fit for Purpose | Big Picture Relevancy | Human-Centric