How NGOs🦏can leverage AI without breaking the bank
How NGOs🦏can leverage AI without breaking the bank
Hello,
This newsletter will take you about 4 minutes to read.
I. Spotlight: How NGOs🦏can leverage AI without breaking the bank
When you think of the kinds of organizations leveraging artificial intelligence (AI), non-government or non-profit organizations (NGOs), do not spring to mind.
It’s the big tech and VC-backed firms that are often seen pushing the boundaries of what’s possible with AI. Limited in resources and employees’ time, investment in AI may seem to be out of the reach of NGOs.
However, there are examples of non-profit organizations leveraging AI to achieve amazing results. Just take a look at Wildbook, an open-source platform developed by conservation tech nonprofit, Wild Me.
Wildbook uses AI to identify individual animals by their unique coat patterns or other hallmark features— they help conservationists across the world identify endangered species like cheetahs, whale sharks, and giraffes.
AI is not— and should not— be reserved for only the most profitable enterprises. It can help drive innovation within NGOs and help solve many of the toughest environmental and social problems we face today.
According to this Salesforce report, the use of AI by non-profits is projected to grow 361 percent in the next two years.
But the above example is more of an exception than the norm. The reality is that most NGOs do not tap into AI, or they don’t know where to start. When enterprises with multi-million-dollar budgets are failing to use AI effectively, how can NGOs do this with minimal resources?
Begin with powerful use cases
NGOs should start with the need for AI and ask themselves what they want to do…
II. Industry Roundup:
1. Article: The Next Great Digital Advantage
17 minutes | HBR | Vijay Govindarajan and N. Venkat Venkatraman
Datagraphs capture how people work, play, learn, socialize, transact, travel, and do commercial activities. Companies must create a robust Datagraph strategy that helps develop unique ways to solve customer problems. This idea of tapping into data-in-motion can help companies use data for more than just operational efficiency.
2. Report: Data and AI Leadership Executive Survey 2022
25 min | NVP
As much as 92% of the world’s leading organizations feel that the ‘cultural factor’ is the leading impediment to becoming a data-driven org. Just 8% feel that it’s due to technology limitations. There has been a 22% increase in measurable returns from AI investments over the last year. Read on for more such industry-level trends.
3. Article: Use This 6-Step Approach to Getting Buy-In for Data and Analytics Strategies
05 minutes | Gartner | Laurence Goasduff
CDAOs must strive to get stakeholders’ buy-in for their D&A strategy. They must be able to demonstrate the business value of their initiatives clearly. This article lists a 6-step approach to communicate business outcomes and personal impact to get the required buy-in — focus on the ‘why’ and ‘for whom’, instead of the ‘what’ and ‘how’.
III. From my Desk:
1. Video: Ask this *one* question to save heartburn (and dollars) in your data analytics journey
4 min | LinkedIn
I’ve noticed many firms burn money by investing in advanced analytics run on dirty data. I share a simple yet impactful framework to assess where a firm is in its data analytics journey. The video presents the one question you must ask when faced with a big-ticket data analytics investment.
-> Watch the Video (Featured on LinkedIn News last week 😎)
2. Article: Want To Get Your Team To Adopt AI? Follow These 8 Critical Steps For Success
8 min | Forbes
I share why data science solutions fail to get adopted by enterprise teams. I highlight four areas that require attention while implementing data science. This article provides a detailed 8-step process to improve the adoption of an organization’s AI initiatives with examples.
3. E-Book: Make Insights Actionable with AI & BI
8 min | AtScale
AtScale published a book with contributions from several industry leaders. I’m happy to have written a chapter on the need for a Data & Analytics Strategy (D&A). The piece highlights the need to align D&A efforts with the organization’s business goals and presents the ten critical elements of a winning D&A strategy.
Does this AI rendering of an MS paint scribble count as a new flower species🌸?😀
Thank you for subscribing and reading the newsletter. I appreciate your attention,
Ganes.
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I’m Ganes Kesari. I publish ‘Data-Driven Future’ to help understand how data shapes our world, explore key trends, and explain what they mean for you today. I speak and write to demystify data science for decision-makers and organizations.
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