Knowledge and information professionals manage data and information in organisations as assets to stay productive, competitive, and innovative. K&IM involve organization, creation, usage, and sharing processes using accessible, efficient, and cost-effective technologies. Collins Dictionary defines artificial intelligence as “the modelling of human mental functions by computer programs” and named “AI” the most notable word of 2023 as it “has accelerated at such a fast pace and become the dominant conversation of 2023” (Guardian.com). Report also stated that the interest in Generative AI on Google searches in the previous year from June 2023 to 2024 has doubled (Statista.com). All these mean that there is an imminent need for K&IM professionals everywhere like myself to get onboard with AI.
My aim for this two-part article is to share my AI discovery journey with fellow K&IM professionals, and highlight the current notable AI resources and tools, instead of an exhaustive and a comprehensive list. This first part is about current AI adoption and development of AI strategy including AI tools and platforms. The second instalment will be about Gen AI and data, Large Language Models, machine learning, and prompts.
You can also share your AI projects and experience via the virtual whiteboard hosted on Jeda.ai, the “multimodal generative visual AI workspace” (free sign-up required).
AI adoption stage
AI in K&IM is at its core a new process involving new technologies, and as such it is logical to start with a current state analysis of AI within our organisation, to determine the issues, identify strengths and weaknesses, and create a roadmap.
ChatGPT is said to be the most popular Gen AI tool by web traffic in 2024 (Visualcapitalist.com), and its creator OpenAI revealed the AGI (artificial general intelligence) and their new AI framework consisting of five levels (Seuk-Min Sohn, LinkedIn.com):
- Stage Level 1: Chatbots, AI with conversational language
- Stage Level 2: Reasoners, human-level problem solving
- Stage Level 3: Agents, systems that can take actions
- Stage Level 4: Innovators, AI that can aid in invention
- Stage Level 5: Organizations: AI that can do the work of an organization
As the relative ‘newcomer’, Google’s Gemini (formerly Bard) ranked after ChatGPT, and the AI Adoption Framework of Google Cloud combines AI maturity themes, phases, and scale to leverage the power of AI.
Microsoft can be seen as a ‘first mover’, its Cognitive Business Competency in the Maturity Model for Microsoft 365 covers AI and machine learning and consists Level 100 to Level 500. “Cognitive Business maturity describes the extent to which organizations have understood, adopted and embedded AI-related capabilities in the right combination to improve and, ultimately, optimize the business” (Learn.microsoft.com):
- Level 100: Initial
- Level 200: Managed
- Level 300: Defined
- Level 400: Predictable
- Level 500: Optimizing
Gartner also offers Artificial Intelligence Maturity Model based on five levels (paid version published in 2020) from the standpoint of research and consulting provider, “to assess level of maturity in using AI technologies and to identify areas for improvement” (Mohsen Semsarpour, Medium.com).
AI tools and platforms
Informed by the insights from current state analysis, we can identify specific gaps and requirements for AI tools and platforms. As AI evolves, the focus of acquirement developed from the uses of AI (Artificial Intelligence For Dummies®, 2022) to organizational problems (Generative AI and LLMs For Dummies®, 2024).
Next, we can develop the AI strategy to navigate complexity and fully benefit from the potential of AI to create value for the organisation (Learn.microsoft.com). As an experiment I asked ChatGPT, Gemini, and Copilot, “what is the best strategy to adopt AI”, and here are the summarised responses (on 7 November 2024):
In Chapter 6 of the book “GenAI and LLMs for Dummies” the author shared “Five Steps to Generative AI” (free download link below):
- Identify business problems
- Select a data platform
- Build a data foundation
- Create a culture of collaboration
- Measure, learn, celebrate
Gartner invites us to “consider the four key elements of any AI strategy and download the GenAI planning workbook to:
- Set GenAI goals, benefits and success metrics
- Tie your GenAI vision to business impact
- Assess and mitigate major AI risks
- Prioritize GenAI initiatives”
These all seem sensible, so “which AI data platform do we choose”, surely that is the million-dollar question? The key is almost certainly to “stay informed about AI trends” (as per Gemini in Figure 3 above) whilst understanding our needs and preparing the data and AI teams, before developing AI strategy and plans. To do so, here are a few better known independent sources (but certainly with human biases):
CB Insights GenAI Research Hub
- Generative AI Resources
- Data Science and Machine Learning Platforms
- Magic Quadrant for Data Science and Machine Learning Platforms (free download via Databricks.com)
- 2024 Gartner® Magic Quadrant™ Leader for Robotic Process Automation (free download via Blueprism.com)
The list literally goes on, so prioritising the problems to determine pilot projects and setting measurable goals for AI trials are almost certainly the first steps to establish and develop AI strategy and adoption roadmap.
Share your AI journey and strategy
Now it’s over to you and please join in the collective learning and share your AI journey by signing up for a free account with Jeda.ai and share your AI projects and experience.
Links
AI Glossary
- Alan Turing Institute Data science and AI glossary
- Coursera Generative AI Definitions: A to Z Glossary Terms (see also this link)
- Council of Europe AI Glossary
- Google Machine Learning Glossary (including Generative AI)
- Linux Foundation Generative AI Glossary of Terms
- MIT Glossary of Terms: Generative AI Basics
- UK Parliament POST Artificial intelligence (AI) glossary
2024 Gartner® Magic Quadrant™ for Data Science and Machine Learning Platforms https://www.databricks.com/sites/default/files/2024-09/magic-quadrant-for-d-799982-ndx.pdf
Artificial Intelligence For Dummies® (2022) http://www.bobfarley.us/0300lawclasses/310artificialintelligencelaw/Artificial%20Intelligence%20For%20Dummies.pdf
Generative AI and LLMs For Dummies® (2024) (sign up for free copy) https://www.snowflake.com/resource/generative-ai-and-llms-for-dummies/
Reference
https://www.statista.com/statistics/1367868/generative-ai-google-searches-worldwide
https://www.visualcapitalist.com/ranked-the-most-popular-generative-ai-tools-in-2024
https://www.linkedin.com/pulse/openais-new-5-stages-ai-development-agi-adoption-sohn-cfa-wckfc
https://openai.com/index/planning-for-agi-and-beyond
https://services.google.com/fh/files/misc/ai_adoption_framework_whitepaper.pdf
https://medium.com/@mohsen.semsarpour/gartner-ai-maturity-model-2c01fab629b6
https://www.gartner.com/en/information-technology/topics/ai-strategy-for-business
https://www.databricks.com/sites/default/files/2024-09/magic-quadrant-for-d-799982-ndx.pdf
Author Biography:
June is a data, information, and knowledge assets manager, an information specialist partnering with the business in capability management. She has experience in knowledge and learning culture, continuous improvement, and automation (including artificial intelligence) for the future of work. She is a native Chinese speaker with keen interest in coaching, walking, writing, and calligraphy.
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