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Check out the updates from this week! Please take a moment to share them with a friend or colleague who might benefit from these useful insights!

Today at a Glance:

• Generative AI Maturity Framework: A Clear Path to Growth
• Generative AI Use cases in the Public Works Departments
• AI Weekly news and updates covering newly released LLMs
• Courses and events to attend

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Tool for assessing Generative AI maturity within an organization

Over 2 years into the LLMs era, few organizations were bullish on taking up AI in business processes very quickly, and few took it in a phased manner to wait-and-see approach.

Six months ago, a common question was asked about which phase or stage my organization is at for adopting Generative AI.

Similar to this situation, I had a chance to work with the leadership of two organizations that, before starting any AI project, wanted to conduct an AI maturity assessment similar to how they conducted Digital Maturity assessments or assessments of several other business functions.

I put forward my views that it's too early to do such a maturity assessment for the AI projects, as the reality has just started with over one and a half years with the speed of adoption primarily on Generative AI.

We discussed it, and their point was that even if it is new, we should conduct an assessment that will reveal some hidden areas and gaps that need to be addressed before starting this ambitious journey.

I also like the notion, and here is below the method that was followed; now, there are several AI maturity assessment frameworks available, and those are also covered at the end of this article; whatever suits your organization, based on your access to these frameworks, you can use them.

It is an AI maturity assessment framework tailored to evaluate an organization’s generative AI maturity. It extends traditional AI maturity dimensions with criteria unique to generative models, such as prompt engineering, responsible output generation, and integrating advanced generative capabilities into products and services.

We have used this one, which was created mutually with their inputs. I am publishing this with their permission, slightly making it generic.

Generative AI Maturity Framework: Structured Guidance for Effective Integration

The Generative AI Maturity Framework addresses the challenge of inconsistent adoption and scaling of generative AI within organizations. It is designed for business leaders, AI teams, and decision-makers striving to integrate generative AI effectively into their operations.

The framework provides structured guidance, enabling precise evaluation and measurable improvement of AI capabilities.

Framework Overview - Dimensions

Each dimension includes criteria focusing on generative AI-specific considerations.

Framework Overview - Levels

The Generative AI Maturity Levels provide a structured approach to assess and advance an organization’s capabilities. Each level highlights key milestones, from initial experimentation to achieving transformational impact, ensuring a clear path for scaling AI effectively and responsibly across business operations.

Call for Action:

Are you getting into a situation where you need to do your organization's Generative AI maturity Assessment?

Share your views, and I will publish all the artifacts to the AI Tech Circle portal.

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Several common AI maturity assessment frameworks are available from the world's leading organizations. Seven are covered in this newsletter's "Things to Know" section.

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Weekly News & Updates...

Last week's AI breakthroughs marked another leap forward in the tech revolution.

1. 12 Days of OpenAI, announcing new features/products - Project in ChatGPT, Advanced voice with video, ChatGPT in Apple Intelligence, Canvas, Sora, OpenAI's Reinforcement Fine-Tuning Research Program, and o1 & ChatGPT Pro. link
2. AI system to generate 3D worlds from a single image from World Labs link​
3. Luma AI releases Luma Photon, text-to-image models. Photon and Photon Flash are creative, personalizable, intelligent visual models for creatives and high-quality image generation. link​
4. Amazon announced Amazon Nova, a new generation of state-of-the-art foundation models (Nova Micro, Nova Lite, Nova Pro, and Nova Premier) link​
5. Veo and Imagen 3: new video and image generation models from Google link​
6. Gemini 2.0 is a new model from Google, and it supports multimodal output like natively generated images mixed with text and steerable text-to-speech (TTS) multilingual audio. link​

The Cloud: the backbone of the AI revolution

• Introducing the Llama 3.3 model on the OCI Data Science link​
• NVIDIA Research Model Enables Fast, Efficient Dynamic Scene Reconstruction. QUEEN, the model supports low-bandwidth, high-quality scene generation that could be used for streaming applications, including industrial robotics operations, 3D video conferencing, and live media broadcasts. link​
• Safeguarding AI against ‘jailbreaks’ and other prompt attacks link​

Generative AI Use Case of the Week:

Urban planning is evolving with the integration of Generative AI, offering innovative solutions to design challenges. Public Works Departments can now capitalize on the power of large language models (LLMs) to generate tailored urban design proposals for parks, housing layouts, and public spaces. These AI-driven suggestions streamline planning processes while aligning with community needs and sustainability goals.

To access the library of Gen AI Use cases, link here:

Chief AI Officer (CAIO) Corner:

Chief AI officers made enterprise inroads in 2024 link​

DOD's Chief AI Officer Launches Rapid Capability Cell, Frontier AI Pilots to Accelerate Adoption of Cutting-Edge Tech, focusing on initial Frontier AI pilots that will apply generative AI models to warfighting and enterprise management use cases. link​

Favorite Tip Of The Week:

Here's my favorite resource of the week.

The University of Cambridge's "​Refreshing the UK’s Strategic Approach to AI​" report highlights the need for a cohesive and forward-thinking strategy to maintain the UK's leadership in artificial intelligence.

It emphasizes investing in AI talent, fostering innovation through research, and ensuring responsible AI development aligned with ethical principles. Key recommendations include enhanced collaboration between academia, industry, and government and prioritizing AI applications that deliver public and economic value. The report calls for a refreshed national AI strategy that balances technological progress with societal trust and governance.

Potential of AI

Aampe Raises $18 Million To Scale Personnalisation With Agentic AI - Forbes​

Vapi Dials-in $20M in Series A Led by Bessemer to Bring AI Voice Agents to Enterprise link​

Things to Know...

Below are several commonly referenced AI maturity assessment frameworks.

Each offers a structured approach to evaluate how organizations adopt and scale AI capabilities.

1 - Gartner’s AI Maturity Model

Provides a five-level progression from Awareness, Active, Operational, Systemic, and Transformational.

Assesses technology readiness, data quality, skill sets, use case breadth, and governance.

It helps map the current state and identify the following steps to scale AI.

(Source: Gartner)

2 - Forrester AI Maturity Model

It defines four stages: novice, experimenter, practitioner, and expert.

Focuses on organizational readiness, data engineering, analytics culture, and business integration.

It helps firms understand their maturity relative to peers and guides strategic planning.

(Source: Forrester)

3 - IDC AI MaturityScape

Outlines a spectrum from Ad Hoc, Opportunistic, Repeatable, Managed, and Optimized.

Considers leadership support, data management, risk controls, skills, and best practices.

Emphasizes continuous improvement, scalability, and alignment with business outcomes.

(Source: IDC, “IDC MaturityScape: Artificial Intelligence”)

4 - Deloitte’s AI Maturity Framework

Deloitte's AI Maturity Framework is a structured model designed to help organizations assess and enhance their AI capabilities.

It emphasizes a holistic approach, focusing on key dimensions such as strategy, talent, data, technology, and operations. The framework categorizes organizations into different maturity levels, guiding them through initial AI experimentation to achieve transformational AI integration.

Measures progress from exploration to sophisticated, integrated AI ecosystems.

Emphasizes value realization and trust in AI-driven decision-making.

(Source: Deloitte)

5 - MIT Sloan Management Review AI Adoption Framework

Identifies phases based on how firms use AI: isolated pilot projects to enterprise-wide transformation.

Focuses on leadership engagement, workforce enablement, data infrastructure, and ethical use.

Guides organizations in evolving from experimentation to fully integrated AI.

(Source: MIT Sloan Management Review, “Expanding AI’s Impact With Organizational Learning”)

McKinsey's AI Transformation Framework: Outlines five stages - Ad-hoc, Localized, Integrated, Enterprise, and Embedded

6 - MITRE’s AI Maturity Model

Defines a framework and assessment method to evaluate an organization’s AI capabilities and practices.

Focuses on six domains: Strategy, Data, Technology, Workforce, Governance, and Continuous Learning.

Progresses from foundational experimentation through integrated, enterprise-wide AI adoption.

Emphasizes trust, responsible use, risk management, and alignment of AI with mission objectives.

(Source: The MITRE AI Maturity Model and Organizational Assessment Tool Guide)

7 - TM Forum AI Maturity Model Toolkit

Provides a structured method to assess and improve AI adoption in telecommunications and digital services.

Covers core dimensions like strategy, governance, data management, technology, skills, and processes.

Maps an organization’s progression from initial exploration to fully integrated, AI-driven operations.

Includes practical tools, measurement criteria, and best practices to guide incremental enhancements.

Aligns AI initiatives with business objectives, operational efficiency, and improved customer experiences.

(Source: AI Maturity Model Toolkit)​

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The Opportunity...

Podcast:

• This week's Open Tech Talks episode 150 is "Tips for Adopting AI and LLMs in Business: Lessons from Michael Vandi," The CEO of Addy AI

Apple | Spotify | Amazon Music ​

Courses to attend:

• Unwrap 12 days of training to learn generative AI this December from Google link​

Events:

• ​AI Everything GLOBAL, Feb 4-6, 2025, Dubai, UAE
• ​

Tech and Tools...

• ​TEN Agent: Real-time conversational agent powered by TEN
• ​Openpilot is an operating system for robotics

Data Sets...

• The Screen Annotation dataset consists of pairs of mobile screenshots and their annotations. The mobile screenshots are directly taken from the publicly available Rico dataset.

Other Technology News

Want to stay updated on the latest information in the field of Information Technology? Here's what you should know:

• Google CEO talks about the future of AI, Waymo, and quantum computing, as published by SEMAFOR​

Join a mini email course on Generative AI ...

​Introduction to Generative AI for Newbies​

Earlier week's Post:

And that’s a wrap!

Thank you, as always, for taking the time to read.

I’d love to hear your thoughts. Please reply and let me know what you find most valuable this week. Your feedback means a lot.

Until next week,

Kashif Manzoor

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