Green IT Archives

October 26, 2009

Green IT: One Path to a Green Recovery

[This post first appeared on a Climate Savers Computing Initiative site. I'll skip the general intro to the greening topic from the original...]

...Five areas of the business are ripe for quick paybacks from green thinking: facilities (heating, cooling and lighting), fleet and distribution, waste, telework, and IT. Let's look at IT specifically and why companies are still going green.

When industry analyst Gartner Group estimated that information and communications technology was responsible for 2 percent of global carbon emissions — equal to the entire aviation industry — most people outside the IT world (and many inside it) were shocked. At the core of these numbers lies the shocking inefficiency of data centers.

Of all the energy going into a modern server farm, IBM estimates, less than 4 percent actually processes something you know, what the room was built for. The other 96 percent of electrons are lost at three stages: (1) cooling the room itself, (2) cooling the stacks or "blades" of servers, and (3) keeping idle machines humming. Most of this energy is wasted and costs real money. In recent years, the share of a data center's variable cost going to energy has grown fast. What was once a tiny part of the budget is now 40 or 50 percent of the operating cost. Over the life of a server, you can easily spend twice as much on electricity as on the capital cost of the server itself.

In response, the competition has been fierce to tackle those three stages of the problem and find ways to slash the energy budget. First, look at the design of the data center itself. One of my favorite "head-slapper" strategies in all of the greening movement is the use of outside air economization — that is, effectively opening the door and letting hot air out rather than cooling it — which Intel estimates can save $3 million in a 10 mega-watt data center.

Second, companies are looking at the server hardware. They're shutting down orphaned systems — Sun discovered during its "Bring Out Your Dead" day that 4,100 of its servers were unused, but plugged in sucking energy. But sometimes, as the Wall Street Journal suggested earlier this year, "the smartest thing to do is invest in new, more efficient systems." One company, Fair Isaac Corporation, bought new, more efficient servers and cut the total number in its data processing center in half. This requires some capital expenditure, but the paybacks can be fast.

Third, software companies are vying to help handle server loads and increase the average 20 percent utilization rate (meaning, 4 of 5 servers are basically idle, waiting for peak loads). The buzzword is virtualization, or using software to create pseudoservers that run in parallel on the same physical server and use all that idle processing power.

For companies using all of these tactics, such as Microsoft, newer datacenters can use 50 percent less energy than ones built just a few years ago. And that's just the large IT systems. Many organizations are now utilizing software to control all the PCs sitting on desks, putting them to sleep overnight and often saving millions. None of this pressure to cut back on IT energy and cost is going away. Forrester reported in January 2009 that 60 percent of IT managers are using green criteria in their procurement decisions and that even in tight times more managers are accelerating green IT efforts than slowing them down.

But what's the most powerful thing you can do to reduce IT energy use? Every time I speak to tech companies or sustainability execs, I hear one theme over and over: The people who create the energy use don't have a clue how much it's costing. The prescription: Add the power bill to the CIO's budget.

December 10, 2009

Gathering Green Data: Tools and Tips

A couple posts ago, I talked about the ways you can use green data — footprinting information on your products and services up and down the value chain — to create enormous value for your company. As they say, you can't manage what you don't measure. And those with the best information can cut costs, reduce risk, answer customer questions on environmental and social impacts, and help customers reduce their footprints.

But it's a fair question to ask how you might gather this data, especially when budgets remain very tight as the economy gradually recovers. Conducting a full, detailed lifecycle analysis (LCA) is likely to be a time-consuming, resource-draining affair. But luckily there are some shortcuts. Here are a few principles and guidelines for getting smarter about your footprint with the least resources possible:

1. Qualitative analysis is good. In fact, it's better to start with a more strategic view on your products or services than to dive right into detailed numeric analysis. Map out your value chain for a quick view on resource use. Then ask really top level questions that aren't part of the normal day-to-day thinking for most functions in a company, like what comes in the door, and what did it take for suppliers to produce it (are there processes energy or water intensive, for example)? What do we do with our inputs, and how much energy and resources do we use? How much energy and resources do our customers use? What happens to our products after customers are done with them?

You're looking for directionally-correct answers on where the biggest risks and opportunities are...or at the very least, where your data gaps are and how best to fill them.

2. "Back of the envelope" analysis is also okay. Top-line numbers on your own impacts and energy use, from departments like IT, facilities, and distribution, can give you sense of where cuts are most needed or valuable. The data may not be readily available at first, but it certainly isn't capital intensive to find it.

3. Use data that's already out there. A truly detailed LCA is, frankly, a pain. Following a product through every stage of its creation and use is difficult. Luckily, the resources available to help you are multiplying. Industry groups and academics have conducted LCAs on many products. You can extrapolate numbers from similar categories to save time and at least understand where the biggest issues lie. For example, let's say you produce food products, some of which have a big dairy component. The dairy industry has conducted an extensive LCA on a gallon of milk. That study can tell you that the methane produced by livestock may dominate your life-cycle carbon footprint as well.

Another option: public (or quasi-public) databases. See the wonky-sounding Economic Input-Output Life Cycle Assessment (EIO-LCA) data at Carnegie Mellon, or the data collected by AMEE in the UK. Without going into too much detail, the EIO-LCA captures data on flows of goods in and out of all sectors of the U.S. economy, along with data on energy use in each sector, and allows for big picture estimates on impacts. It's a back-of-the-envelope calculation — on a very big envelope. But if you don't want to dig into databases yourself (and who does), then you'll be glad to know that some smart developers have embedded these data sources into handy software products, so...

4. Seek out tools to help you. There is also a wealth of options for software that can help you get a handle on your impacts, including those throughout your supply chain. There are a few now classic providers of product LCA software, such as Ecobilan's TEAM and GaBi Sofware. But new niche players and products that focus on a company's carbon footprint include offerings from both the usual suspects and new entrants: Carbon Impact (formerly Clear Standards, now part of SAP), Planet Metrics, SAS for Sustainability Management, Computer Associates eco-Software, and two open source solutions Carbon Counted and Earthster (in beta).

I've worked with, or been taken through demos of most of these players — all are offering good tools and expertise. But I'm sure I've missed many others so please send me tools you've found useful (

On top of these carbon modeling tools, companies are offering a range of other green data-tracking services: a sustainability dashboard from Microsoft, Google PowerMeter to measure energy consumption (for homes, but how far off are business-targeted versions), and a cool new product from AngelPoints (working with Saatchi S) that puts the Wal-Mart Personal Sustainability Project program into tracking software so companies can show employees what all their pledges of behavior change add up to.

Beyond these more self-help methods, there is an ever-growing number of consultants that can guide you (including partners of mine such as Domani). You may need to start small with my guidelines above and estimate if resources are too tight, but if you can, working with experts can provide you with a much deeper picture of your company's data-gathering capabilities.

Finally, a larger investment in getting smarter — building that internal capacity to understand footprints on an ongoing basis, and even real-time — will pay back in ways you can barely imagine. Those with the best data win.

This first appeared on Harvard Business online.

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January 22, 2010

Top 10 Green Business Stories of 2009

Happy New Year all (ok, I'm a bit delayed, but I entered the new year and promptly got really sick -- lost over a week in there). So let's start fresh now!

Anyway, I took a bit of time at the end of 2009 and early 2010, with a couple weeks' perspective, to think about the stories that really grabbed me in 2009. The top 10 is below, but see my brief write-ups and logic on each at my e-letter site here.

1) Copenhagen fails or does it?
2) The debate over climate science rages on (in the U.S. at least)
3) The EPA steps in
4) Wal-Mart keeps the pressure up (and saves the rainforest?)
5) Domino's employees deliver a new kind of openness.
6) IBM starts building a "smarter planet"
7) GM goes bankrupt
8) Some of our biggest capitalists get serious about carbon
9) China emerges as a green tech leader and the world's biggest emitter
10) The bottom of the pyramid becomes a source of innovation

And the bonus, theater of the absurd, wacky story...
10 1/2) Forbes names Exxon green company of the year

June 2, 2010

SAP and the Greening of a Service Business

It's always easier to picture how a manufacturing company can go green — just cut back on energy, waste, and material to reduce air and water pollution, for example. But what does it mean for a service-focused business, such as a software company, to travel down the sustainability path?

Last week I got an interesting view on how enterprise software giant SAP is pursuing a green agenda. Sustainability was a core theme at SAP's annual meeting SAPPHIRE NOW, a large gathering of over 16,000 CIOs and tech professionals. (Full disclosure: SAP hired me to speak at the event.)

So how does a company with a seemingly small physical footprint create real value from pursuing sustainability? SAP seems to be pursuing three paths that are a good framework to keep in mind.

First, walk the talk. SAP is first reducing its own impacts. Last year, the company saved $90 million Euros through eco-efficiency, including a 7% reduction in energy consumption. A good portion of the savings came from reducing air travel, which makes up 35% of the company's total carbon impact. SAP also got lean in its IT operations; for the first time ever last year, it had fewer servers when the year ended than when it began.

SAP also worked to engage employees and tackled some smaller, symbolic issues like paper use. Sustainability managers placed large stacks of empty paper boxes in the cafeteria to demonstrate how much employees used in a single day. The company has also asked its 50,000 employees to take "100,000 steps" (that is, two each, or one for each foot) to be more sustainable in their lives.

Second, and far more importantly, help your customers reduce their impacts, a core greening strategy for any company. As co-CEO Jim Hagemann Snabe put it during his keynote, SAP wants to be "an Enabler." Snabe continued, "We believe transactional systems we have installed in many customers have information that...can help customers manage resources — not just human capital, materials or money but scarce resources like water, energy and CO2...This is the mission we have taken on with sustainability."

SAP took a hard look at its product line to see if it could deliver on this vision. In the last year, the company acquired Clear Standards, a well-respected carbon footprint software company (rebranding it Carbon Impact), and announced it will purchase Technidata, a leading provider of environmental, health, and safety management software. Last week, SAP execs were running around the show floor, gleefully demonstrating how cool Carbon Impact looked on an iPad, and demonstrating how it helps SAP analyze its own footprint data.

As an example of how SAP envisions working with companies to enable sustainability goals, execs describe how the company helped oil refiner Valero harmonize its operational systems. By obtaining much better information on energy use and processes across the organization, Valero was able to save $120 million in energy costs last year (and an expected $200 million-plus in 2010) and slash environmental incidents 63% since 2006. The savings realized from having better data available is a perfect example of the "Prius effect" that I've written about before.

By working in this way with their customers, SAP is able to reduce impacts and create value far beyond what it could just do internally.

Third, communicate clearly with customers and stakeholders about how your products and services help the cause. SAP has developed a view on the key operational focal areas that companies need to manage well to head down the road to sustainability. The company created a "Sustainability Map" that includes 33 topics — such as sourcing, logistics, design, and green IT - across 8 functional areas of the business. These topics map to some broad goals that SAP argues drive sustainable value creation (such as reducing operation risk and improving resource productivity).

The map is a critical part of the company's new CSR report, an innovative, social-media-driven approach to both discussing the company's impacts and pitching its solutions. This dual-purpose report makes sense for a service business.

Dr. Peter Graf, the company's Chief Sustainability Officer, put SAP's shift in large, strategic terms and made it clear that providing customers with solutions was critical to the company's future: "When we look at sustainability we compare it to other fundamental megatrends [such as] globalization and the Internet. Sustainability is going to be similar in the way it fundamentally changes all business as the leader in business process technology, we have to play, and we have no choice but to lead." (See a streaming video of an interview with Peter Graf and me here — you'll have to register, and then look under "keynotes and broadcasts").

For many years, IT companies felt that they didn't have a lot of skin in the sustainability game — they didn't have big smokestacks, after all. But now even service companies like SAP are seeing the deep connection between green and business growth survival.

[This post first appeared at Harvard Business Review Online]

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March 6, 2011

Cloud Computing is Greener

Cloud computing is all the rage. In its simplest terms, it means outsourcing your company's information technology (IT) needs, from data and storage to software. All the servers and applications sit elsewhere in the Internet "cloud," but more literally in a data center or centers.


A recent study from Microsoft (with Accenture and WSP), "Cloud Computing and Sustainability", compared the environmental footprint of running business software internally or with an outsourced provider (in this case, Microsoft). The study showed that, compared to running their own applications, by outsourcing companies can reduce the energy use and carbon footprint of computing by up to 90 percent!

This is very good news. IT is one of the fastest growing energy hogs, accounting for at least 2 percent of global energy use. In my last book, Green Recovery, I focused on IT as one of five operational areas where green initiatives help companies save money quickly (the others were facilities, distribution, telework, and waste).

In the book, I cited statistics from IBM showing that less than 4 percent of the energy going into a data center is used to process something.


While the IT world has gotten a lot more efficient lately, there's still much room for improvement. And apparently moving your applications to the cloud can help immensely.

According to the Microsoft report (see page 6), cloud computing drives energy reductions in four related ways, which boil down to a few key leverage points:

  • Reducing excess capacity
  • Flattening peak loads
  • Employing large-scale "virtualization" software
  • Improving data center design.

Using the cloud addresses all three of the major energy loss areas in the IBM chart: data center design tackles room and server cooling, while the other scale benefits mainly address the absurd waste, in percentage terms, from server underutilization (the far right bar).

Rob Bernard, Microsoft's Chief Environmental Strategist, likens the cloud to mass transit: "A data center essentially gets computing applications to carpool or take the bus instead of sitting in their own individual servers...but unlike mass transit vs. private vehicles, there is no tradeoff for convenience and on-demand availability."

So all of this is pretty logical. Scale is more efficient and allows for better resource planning. But I'd offer a few points worth thinking about, and one note of caution.

  1. The centralization of computing power should look familiar. To get some perspective on the study, I spoke with Mark Monroe, the new Executive Director of Green Grid, an organization dedicated to making IT more energy and carbon efficient. He compares the cloud to the electric grid, citing Nicholas Carr's book, The Big Switch, which Monroe says "compares utility computing development to the emergence of centralized electrical generation in the early 20th century." Like electric plants, Monroe says, central computing "utilities" benefit from scale and high utilization.
  2. In this case, outsourcing is another word for "servicizing," or turning a product into a service offering. In theory, a service provider will strive to keep its costs down, thus using as little energy and resources as possible. Cloud computing fits this model well (and fits a general transition to helping customers use less). As Monroe says, "Cloud providers want to provide an hour of CPU time, a Gigabyte-month of storage, a CRM transaction, an email, or a web page for as little cost and as high a margin as possible. That just has to lead to higher efficiency than someone focused on delivering a feature internally."
  3. Small companies get the biggest bang for their cloud bucks. The study's most fascinating finding is that the larger IT users get less benefit out of working with Microsoft's cloud. For organizations with over 10,000 users, the reduction in GHG emissions is healthy 30 percent. But that pales in comparison to the 90 percent reduction firms with just 100 users can attain.
  4. Smart outsourcing, scale, and technology can help other parts of the business be more efficient also. For example, I talk in Green Recovery about the benefits of telecommuting and telepresence, and in distribution, larger carriers can ensure fuller, more efficient trucks, rail cars, and ships.
  5. But, keep one thing in mind when outsourcing an energy-using function: the footprint is still yours. Technically, a company's main footprint includes only its own facilities (in wonky terms, that's "Scope 1 emissions"). But I believe that anyone doing contract work for you — which is not really the same as traditional suppliers - should count toward your footprint.

In short, finding providers and partners that can take some of your energy-using operations to scale, and manage them in a shared capacity, is good for your footprint and your bottom line.

(This post first appeared at Harvard Business Online.)

July 28, 2011

A New Green IT Report from CDP

Just a quick heads up about a nice, pithy report on how cloud computing can reduce the large, and growing, IT energy footprint.

"Cloud Computing - The IT Solution for the 21st Century" comes from one of my favorite agitators for transparency and climate action, the Carbon Disclosure Project.

Fyi, there's a short piece I wrote in the report, most of which is taken from this blog from earlier this year, "Cloud Computing is Greener."


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January 7, 2013

A New Algorithm for Fast Carbon Footprinting

(Happy New Year all...I forgot to post this one last Fall...)

Low-cost carbon footprinting is a Holy Grail for the sustainability world. But how do you measure your footprint at multiple levels — from products to business lines to the whole enterprise — quickly and cheaply? Over the last few years, PepsiCo has been working with partners at Columbia University to solve this interesting and complex business problem. The results of this partnership, what the team is calling a "Fast LCA" process, are emerging. And they're encouraging.


To understand this initiative better, I recently spoke with two PepsiCo executives working on sustainability, Al Halvorsen and Robert ter Kuile, and the academic brain trust at Columbia led by adjunct professor Christoph Meinrenken. Here's what I learned about three major issues:

1. Why do carbon footprints matter for your business?

Understanding your carbon footprint is a required skill of 21st-century business. Customers, consumers, employees, and investors (like the increasingly influential Carbon Disclosure Project, backed by institutions with $78 trillion in assets) want to know your contribution to — and actions to solve — this global challenge.

But it's not just about reacting to pressure.Knowing your footprint helps you get proactive, spot risks and costs along your value chain, and identify opportunities to innovate. Getting smart about green data makes money. In essence, carbon is a proxy for energy cost and waste, and good carbon management is a proxy for good operational execution.

2. In layman's terms, what have Columbia and PepsiCo accomplished, and how?

The detailed methodology behind this advancement is complicated: for the math and data wonks out there, see this short but dense article in the Journal of Industrial Ecology.

But for even layman like me, the problem is clear: To use carbon data to reduce costs and risks throughout the value chain, you need know the footprint of every single product that contributes significantly to your bottom line or brand. Conducting a detailed lifecycle assessment (LCA) is, to put it mildly, a resource-intensive exercise.

As Meinrenken and the Columbia team suggest in their Journal article, a full LCA for even a relatively straightforward consumer product like a can of soda would require data on

"...the masses of three packaging materials and five ingredients, transportation distances of all materials to the plant, amounts of four types of energy, transportation distances to stores, refrigeration times in stores and at home... and then all materials and activities have to be paired with respective EFs (carbon emission factors), bringing the total count of individual [data] inputs to approximately 100 for a single product alone."

LCAs for an entire product portfolio would require thousands of often hard-to-get data points. It's tough to justify this level of investment. PepsiCo's ter Kuile put it succinctly: "there's no way to look at all of our products at this level of detail in any reasonable time frame."

So what has Columbia done? I'm not doing it justice fully, but it's about algorithms and shortcuts. They start with internal operational data from existing SAP and Oracle databases - bills of materials (packaging, ingredients, and so on) on every single product, as well as shipping, energy, and water data for every plant. But instead of collecting an exact carbon emissions number from every supplier of those materials, they use statistically generated emissions factors (EFs), which provide good estimates on carbon for common inputs like sugar or corn. Modeling EFs is what saves the most time.

Other shortcuts draw assumptions on systemic issues like transportation distances, refrigeration time in transit or in the home, and recycling rates, all of which influence the footprint.

Then the model does something critical: it runs a sensitivity analysis to identify the inputs where variation could cause a meaningful change in the ultimate calculation. Thus the model helps managers zero in on data that's worth spending more time to get right. Let's say the model assumed that soda in France sits in the store refrigerator for two days instead of four. Does that number impact the total footprint very much? If so, managers can do more research and find better numbers (that is, more "primary" data).

(Note: for another interesting take on this process that likens the whole thing to a "Facebook-inspired carbon calculator," see Allison Moodie's piece on

Finally, the model makes assumptions about elements like packaging that may be common across many products. This is where it gets even more interesting for PepsiCo since it allows execs to explore "what if" scenarios. Which brings me to #3:

3. What's the business value for PepsiCo and all companies with broad product portfolios?

As PepsiCo's Halvorsen told me, "the real reason you do an LCA is improve the business... to put more efficient processes in place and innovate in the supply chain."

To see how this works in practice, let's go back a few years to the beginning of the PepsiCo/Columbia working relationship. The team produced a fascinating study on Tropicana orange juice, which concluded that the biggest contributor to the carbon footprint was not manufacturing or transportation, but natural gas-based fertilizer. For essentially no cost, PepsiCo could eliminate a third of Tropicana's carbon footprint — and all the potential cost and risk associated with it — by switching to non-fossil-fuel-based fertilizer (their test farms are a few years into their experiment).

This exercise was so helpful, PepsiCo's executives wanted to gather this level of strategic knowledge across the business for all products. To test Columbia's new fast LCA model, they submitted data on two different parts of the business: the beverage business in China and the snack business in Brazil.

What makes this story interesting is what PepsiCo can do with the information at the product and business unit level — and it's not to get an exact number of grams of carbon per bag of chips, which is fairly meaningless to consumers anyway. The real goal here is to pose "what ifs" and find the quickest, most profitable way to reduce impacts and improve efficiency.

These execs want to ask questions such as, "If we reduce packaging in one product, what does that do for other products that use the same packaging elements? What do we save in carbon, material, and money?" They've begun this process, but it's still the early days. Over the next year, I hope to report on some operational changes that were made and measured.

A final thought on what's required to make this happen: To avoid the old "garbage in, garbage out" problem, you need good data. PepsiCo knows a lot about its business — from the precise formulations of every product (to estimate supply chain impacts) to the exact production rates for each facility (to accurately allocate energy use for every product). In essence, the innovation here is combining really good, so-called "big data" with really good algorithms.

There's a lot at stake here in dedicating scarce resources well. Getting carbon footprints right is a critical step on the path to healthy brands, higher profits, and a livable planet for all of us.

(This post first appeared at Harvard Business Online)

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May 14, 2018

Using AI to Help the World Thrive

(I've gotten behind on re-posting my articles! I'll try to catch up in the next couple of weeks. As part of my new column in MIT Sloan Management Review, I've been diving into the world of new technologies and how they enhance or interact with the sustainability agenda. This is an article about AI, with a focus on Microsoft's efforts. More tech to come soon...)


What is the purpose of artificial intelligence?

The hype about AI, with its massive potential to disrupt business and society, is likely true. AI could make business radically more efficient and answer questions we didn’t even know we had. Of course, it may also destroy millions of jobs as machines get better than humans at everything from driving trucks to analyzing CT scans.

But focusing for the moment on the upside, it’s worth asking: Could AI help humanity solve its biggest problems?

Consider the challenges in front of humankind. We need to build a thriving economy and world for what the United Nations predicts will be 9.8 billion people by 2050. And we must do it without overwhelming our natural resources or making our climate uninhabitable. We’ll need dramatic changes in how the world works — deep shifts in energy, transportation, buildings, manufacturing, food and agriculture, and much more. We need to answer questions such as:

  • What’s the best, most economic path to a low-carbon economy?
  • How do we feed 9 billion or 10 billion people on a planet with a fixed amount of arable land?
  • How can we best move billions of people around crowded cities to keep those cities functioning, while using the least fuel possible?
  • How do we manage an electric grid with huge amounts of intermittent renewable power and billions of smart devices and electric vehicles plugged in?
  • How can our economic and political systems enhance well-being for all and reduce inequality?

We may need some serious help answering these kinds of questions. It’s quite possible that we’ve created complex, systemic problems that exceed our human capacity to solve them. In other words, AI may not just be nice to have; we may need it.

Some companies, particularly the tech giants, are recognizing this reality. They’re looking to AI as a tool for solving environmental and social problems.

For example, Google asked its DeepMind AI to examine the “complex, nonlinear” problem of how it uses energy in Google’s data centers (and this is no small issue: just in the United States, the tech sector’s data centers use 70 billion kilowatt hours of electricity at a cost of $7 billion per year). Google’s AI was able to slash energy use for cooling by an impressive 40%, saving significant money and carbon emissions.

In 2014, IBM launched a 10-year, $100 million project to use its Watson cognitive computing system to help Africa solve business and social challenges. The company is also leveraging AI to forecast solar and wind availability for power generation.

Enter Microsoft’s $50 Million “AI for Earth” Program

But perhaps most intriguing is the initiative that Microsoft recently launched — its own big play for leadership in the realm of “using AI to save the world.” In December, the company announced an expanded commitment of $50 million to, as Microsoft President Brad Smith wrote in a blog post, “put artificial intelligence technology in the hands of individuals and organizations who are working to protect our planet.” Smith pointed out that humanity is collecting a vast amount of data on the state of the planet. We need help, he wrote, to “convert it into actionable intelligence.”

The program, dubbed AI for Earth, is finding and funding innovators who are making progress in four critical areas — climate change, water, agriculture, and biodiversity. Microsoft’s first grantees, 35 teams from around the world, are impressive. The AI pioneers include a group in Italy using images of snow in mountains to better predict snow melt and thus water availability; the Jane Goodall Institute, which is helping “identify chimpanzee habitat connectivity and conservation priorities in Africa”; teams at Yale and Cornell using AI and data to understand crop health and improve yields; and a crowdsourced program, iNaturalist, that combines both “citizen-scientist” data with trained scientist input on biodiversity.

Microsoft will accelerate progress by providing seed money, intellectual support (in the form of a multifunctional team of AI and sustainability experts), and technology aid through its cloud computing resources. The AI for Earth program will also identify the initiatives that have the most promise and offer even more aid.

But the goal is more than creating some isolated success stories — it’s about being a catalyst for greater change. The stated mission of Microsoft’s AI efforts is “to empower every person and organization to thrive in a resource-constrained world.”

Rob Bernard, Microsoft’s chief environmental strategist, tells me that with AI for Earth, “we want to light up the ecosystem — we want the market to explode.” He imagines that once a team has created tools for, say, developing high-resolution maps of farmland from satellite imagery, other teams can build on it. They might ask different questions than the initial group, focusing on a different crop. Or look at a completely different problem outside of agriculture that could benefit from the same AI approach.

It’s a great idea. But a critical component of this “explosion of ideas” plan is making some capabilities part of a publicly available platform. So I have to wonder, what’s in it for Microsoft?

Business Payoffs for Being a Leader in Solving the World’s Problems

I see a few primary business benefits.

First, the initiative may help Microsoft attract and retain the best people. The competition for AI talent is intense and the tech giants are paying big bucks. Bernard says that when Microsoft posted some AI for Earth positions, some of the company’s top AI people jumped at the opportunity. There’s a clear trend, especially among millennials, for people to want more purpose in their jobs. Working on big, global environmental challenges is meaningful.

Second, the company can drive revenues for its cloud services. Digitizing the world, which we seem committed to doing, will require lots of data, servers, and software. Putting Microsoft in the middle of that whirlwind is good for business.

Third, the company could yield some related, but harder to measure, intangible benefits. Working on big issues and connecting to cool startups raises the company’s profile and keeps the 40-plus-year-old brand (I know, hard to believe) relevant and modern.

So, this whole movement will be good for humanity and benefit Microsoft (and other tech companies). And that’s more than OK. In fact, it’s critical to the success of the program. We need a large flow of ideas, capital, and talent to solve the world’s biggest challenges. Making it profitable to use AI in the service of humanity will attract more resources to the cause. Again, it’s likely that we need AI. Let’s just hope AI continues to need us.

(This post first appeared in MIT Sloan Management Review here.)

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