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Best of LinkedIn: Sustainability & Green ICT CW 08/ 09 · Best of LinkedIn: Digital Transformation & Tech

• 0:00
  Speaker 1: This episode is provided by Thomas Allgaier and Frennis, based on the most relevant LinkedIn posts about sustainability in green ICT in CW eight-and-nine.
• 0:08
  Speaker 1: Frennes supports ICT enterprises with market and competitive intelligence decoding green software developments benchmarking emerging standards tracking regulatory shifts and analyzing competitor strategies.
• 0:20
  Speaker 0: Right and just to set the expectations right up front for you today.
• 0:24
  Speaker 0: Yeah, we're focusing on sustainability in green ICT trends seen across LinkedIn exactly
• 0:30
  Speaker 1: And welcome if you are joining us today.
• 0:32
  Speaker 1: It means you care about the actual mechanics of the tech We use every day.
• 0:36
  Speaker 1: our mission for you on this deep dive is simple?
• 0:39
  Speaker 1: We are we're cutting straight through the corporate fluff To uncover the operational realities of sustainable digital transformation.
• 0:46
  Speaker 0: yeah combining the engineering The government
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  Speaker 1: market signals Based entirely on curated insights from real practitioners of the last two weeks.
• 0:54
  Speaker 1: So if you're a professional navigating this space, You aren't exactly the right place.
• 0:59
  Speaker 0: it really has been a highly revealing couple of weeks.
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  Speaker 0: What stands out from the sources is a clear maturation in the industry.
• 1:07
  Speaker 1: Oh absolutely
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  Speaker 0: like sustainability and IT Is shedding its skin as just a marketing slogan or an isolated side project, it's becoming a rigorous integrated agenda where we are finally seeing real structural trade-offs being debated openly.
• 1:24
  Speaker 1: Okay, let's unpack this.
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  Speaker 1: The best place to start is the sheer physical weight of the cloud specifically...the massive footprint of artificial intelligence.
• 1:33
  Speaker 0: The green AI paradox?
• 1:35
  Speaker 1: Yes!
• 1:35
  Speaker 1: We are constantly calling it the Green AI Paradox.
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  Speaker 1: It is so easy to think a generative AI prompt as weightless but the physical reality behind screen its incredibly heavy.
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  Speaker 0: To give you a sense of the scale that weighed, Burton Kelso shared a post noting that by twenty-twenty six The data center is powering all those supposedly simple AI requests.
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  Speaker 1: Like generating a dinner recipe?
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  Speaker 0: Right?
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  Speaker 0: or summarizing in meeting they are now using more electricity than the entire country of Japan.
• 2:02
  Speaker 0: think about for second an Entire industrialized G seven nations power grid completely eclipsed by server farms.
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  Speaker 1: That's just difficult to wrap your
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  Speaker 0: head around.
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  Speaker 0: and it isn't Just Power To keep those supercomputers from melting down, they are drinking a staggering amount of water.
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  Speaker 0: Yes often competing directly with local farmers and residents for shared reservoirs especially during droughts.
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  Speaker 1: The water issue is what really caught my eye because it's so hyper-localized.
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  Speaker 1: Chalet Ren shared some research recently regarding the US Water Infrastructure Mismatch.
• 2:38
  Speaker 1: that explains this perfectly.
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  Speaker 1: Ren points out a single data center might request six million gallons of water per day from local authority.
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  Speaker 0: Crazy.
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  Speaker 1: Right, and the bottleneck isn't the national water totals.
• 2:51
  Speaker 1: there is no giant National Reservoir that data centers can just plug into.
• 2:55
  Speaker 0: Exactly.
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  Speaker 0: you cannot easily route water across state lines The way you know.
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  Speaker 0: wheel electricity across a power grid.
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  Speaker 1: It's like trying to fill an olympic swimming pool using single garden hose connected To neighborhood thats already experiencing severe drought.
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  Speaker 1: Water might exist somewhere in country but local municipal pipes And community systems
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  Speaker 0: Burst
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  Speaker 1: under that kind of concentrated strain.
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  Speaker 1: The crisis is entirely about local peak demand.
• 3:21
  Speaker 0: So the immediate question that surfaces, Is how we mitigate this?
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  Speaker 0: Abhishek Karol pushed a very practical solution in his recent post.
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  Speaker 0: What he argues?
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  Speaker 0: that green AI has become measurable down to the individual application level.
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  Speaker 0: You cannot just look at the data center as a monolithic entity anymore,
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  Speaker 1: right?
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  Speaker 1: He needs specifics.
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  Speaker 0: he says you need telemetry to definitively state This specific AI app.
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  Speaker 0: use this much energy and produce this much carbon.
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  Speaker 0: He's advocating for organizations to introduce hard-carbon budgets directly into their procurement decisions.
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  Speaker 1: So if enterprise buyers demand sustainability metrics alongside cost in latency suppliers
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  Speaker 0: will have no choice but to optimize for it.
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  Speaker 1: I understand the logic there But doesn't that create a tracking nightmare?
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  Speaker 1: And Curry offered a perspective that seems to directly challenge the granular approach.
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  Speaker 1: She argues trying to calculate the exact energy cost of single AI query is actually the wrong question altogether.
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  Speaker 0: What's fascinating here, she isn't saying we shouldn't track it... Right!
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  Speaker 0: ...she says we are looking through the WRONG end.
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  Speaker 0: She calls it the ultimate, It-Depends scenario.
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  Speaker 0: On
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  Speaker 1: steroids basically?
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  Speaker 0: Exactly!
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  Speaker 0: The carbon cost of a query depends on this specific model —the time of day... ...the ambient temperature outside the data center… …the phrasing of the prompt—It's
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  Speaker 1: impossible to standardize
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  Speaker 0: Yes.
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  Speaker 0: So instead of microtracking queries she says you should be looking at the macro level – the provider's overall commitments and their grid impact.
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  Speaker 1: Like Google versus XAI
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  Speaker 0: Right She contrasted Google which is aggressively pushing for two hundred forty seven carbon-free energy by twenty thirty four other compute against ex AI, which currently lacks public sustainability targets.
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  Speaker 1: So her point that enterprise leaders should use their consumer power to choose providers with systemic clean energy policies rather than stressing over the wattage of a single chat prompt.
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  Speaker 1: in speaking of Google's systemic policies and on learner Nesbit highlighted there approach infrastructure recently Google is planning a new, eight hundred and fifty megawatt data center powered primarily by co-located solar in wind.
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  Speaker 1: Which
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  Speaker 0: is massive!
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  Speaker 1: It isn't what's notable here that this avoids the typical behind the meter gas turbines?
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  Speaker 1: Just to clarify for anyone listening who might be unfamiliar Behind the Meter usually means private localized power generator
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  Speaker 0: Often a dirty gas or diesel turbine.
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  Speaker 0: Right,
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  Speaker 1: that data center builds on its own property to bypass delays and getting connected to the main public grid by integrating renewables And battery storage directly.
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  Speaker 1: Google is projecting an eighty three percent reduction in emissions.
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  Speaker 1: That
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  Speaker 0: Is A massive Reduction On Paper.
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  Speaker 0: But Infrastructure Decisions Do Not Happen In A Vacuum.
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  Speaker 0: They Happened In A Highly Complex Political And Regulatory Context.
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  Speaker 0: Boris Gamazachikov highlighted a very specific dynamic recently regarding the Ratepayer Protection Pledge.
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  Speaker 0: This is voluntary commitment signed by major tech firms regarding power for data centers.
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  Speaker 1: And just to pause here, to be absolutely clear We are simply reporting the observations from source material here without endorsing any political viewpoint.
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  Speaker 0: Absolutely, we're completely impartial on this.
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  Speaker 1: We just looking at market signals
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  Speaker 0: Exactly!
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  Speaker 0: So Boris points out that while clean energy could technically meet commitments of this pledge The specific political framing of a pledge targets quote-unquote unreliable energy subsidies.
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  Speaker 0: In practice, he notes this particular framing might actually favor the expansion of fossil fuels.
• 6:47
  Speaker 1: Oh so
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  Speaker 0: because it essentially provides cover to build more of those behind-the-meter gas and backup diesel generators you just mentioned rather than waiting for renewable infrastructure to scale.
• 6:56
  Speaker 0: Wow
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  Speaker 1: that completely alters The trajectory of those emission reduction goals.
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  Speaker 1: It does And we are seeing these tensions play out globally.
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  Speaker 1: Dr Daniel CFN and Maria Apple Morales highlighted the core paradox playing out in Southeast Asia right now.
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  Speaker 1: You have Singapore, Malaysia and Indonesia racing to build AI data centers to capture market share.
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  Speaker 1: this is heavily straining local grids that are still deeply reliant on fossil fuels.
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  Speaker 1: but The flip side the paradox This very same AI is being deployed to optimize those regions.
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  Speaker 0: Like running smart building systems?
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  Speaker 1: Exactly, which radically cuts urban energy use.
• 7:36
  Speaker 1: and it's driving precision agriculture that reduces water waste in farming.
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  Speaker 0: It's a delicate balancing act And we have to be incredibly careful about assuming those optimization gains will just save us Right.
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  Speaker 0: Dr.
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  Speaker 0: Sascha Lucioni brought up critical warning of the Jevons Paradox.
• 7:51
  Speaker 0: If you aren't familiar with the Jeffens paradox as an economic principle where technological progress increases the efficiency of a resource, but because it becomes cheaper and more efficient.
• 8:01
  Speaker 0: The overall rate of consumption actually explodes at backfires exactly.
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  Speaker 0: Dr Lucioni points out that the efficiency gains in AI hardware and software are currently being entirely swallowed up by the massive energy rebound effects of generative AI.
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  Speaker 1: we make them models ten percent more efficient
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  Speaker 0: so people use him fifty percent more often
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  Speaker 1: which means we cannot rely solely on the hardware engineers to fix this.
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  Speaker 1: The software developers have to step up.
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  Speaker 0: if
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  Speaker 1: the code running on those servers is bloated, it doesn't matter how green the power source is
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  Speaker 0: right?
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  Speaker 0: Which brings us to Yuna Morgenstern.
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  Speaker 1: Yes.
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  Speaker 1: You know Morgan Stern's thoughts on Green Software and engineering for efficiency.
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  Speaker 1: she made a really compelling plea for minimalism in coding.
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  Speaker 1: I loved her quote.
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  Speaker 1: your business fits on a raspberry PI.
• 8:46
  Speaker 0: It is a great image.
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  Speaker 0: A Raspberry Pi low-power computer, and she uses it to point out how incredibly bloated modern software has become.
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  Speaker 0: Outside of the massive hyperscalars most companies deploy fleeps over engineered microservices just to render a few text boxes on screen.
• 9:04
  Speaker 1: Exactly!
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  Speaker 1: She's championing green code not as some trendy ESG marketing gimmick but as core senior engineering discipline about returning real engineering optimizing compute cycles cutting computational waste.
• 9:17
  Speaker 0: The DEA supports her urgency.
• 9:19
  Speaker 0: Tim Prosser shares some sobering numbers.
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  Speaker 0: The ICT sector currently emits two to four percent of global greenhouse gases.
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  Speaker 1: That puts the tech industry roughly on par with the entire aviation industry.
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  Speaker 0: Yeah, Prossor notes that fundamental architectural choices like choosing compiled languages over interpreted languages can drastically impact that energy footprint.
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  Speaker 1: Let's break that down for a second because I think it is crucial distinction to any developer listening.
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  Speaker 1: Why does the programming language actually dictate energy drawn from grid?
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  Speaker 0: It comes down how computer processes instructions.
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  Speaker 0: Think of compiled languages like translating book into another language once, printing and anyone can read whenever they want.
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  Speaker 1: Highly efficient!
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  Speaker 0: An interpreted language, on the other hand is like having a live translator.
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  Speaker 0: follow you around translating your words On The Fly sentence by sentence every single time.
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  Speaker 0: You speak
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  Speaker 1: that sounds exhausting.
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  Speaker 0: it Is for the machine?
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  Speaker 0: It requires a processor to work much harder Continuously burning CPU cycles which translates directly into burning more electricity.
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  Speaker 1: That makes perfect sense and Lenny Keeloman shared a tangible win regarding exactly this kind of optimization.
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  Speaker 1: She highlighted a green coating pilot conducted by DSM Fermanic and Accenture.
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  Speaker 1: Oh, right!
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  Speaker 1: By stripping out the bloat in focusing on energy efficient software design they save the energy equivalent of driving an electric vehicle all the way from Paris to Bangkok.
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  Speaker 0: That is incredible.
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  Speaker 1: When you translate code efficiency into real world physical metrics like that it suddenly makes the abstract concept of Green Software something whole engineering team can rally around.
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  Speaker 0: It anchors this concept reality And looking toward the immediate future, Anita Schuttler shared some predictions for twenty-twenty six that complicate this even further.
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  Speaker 0: What
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  Speaker 1: does she predict?
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  Speaker 0: She anticipates the massive rise of agentic coding where AI agents autonomously write and speed up software development but she warns if we unleash AI to right code.
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  Speaker 0: it requires strict resource guardrails.
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  Speaker 1: We need systems that automatically select smallest most efficient AI model for a specific
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  Speaker 0: task Yes rather than defaulting into the most power hungry model every time.
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  Speaker 1: She also mentioned local AI,
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  Speaker 0: didn't she?
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  Speaker 0: Yes.
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  Speaker 0: And that is a massive trend.
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  Speaker 0: instead of sending every single prompt to a centralized... energy-hungry cloud data center.
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  Speaker 0: Local AI means running smaller, highly specific models directly on edge devices
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  Speaker 1: like your laptop or phone or a local server.
• 11:46
  Speaker 0: exactly.
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  Speaker 0: it boosts data privacy reduces reliance on proprietary tech giants and utilizes whatever local decentralized green power you might have.
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  Speaker 0: It essentially bypasses the massive datacenter transmission bottleneck entirely for everyday tasks.
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  Speaker 1: Here's where it gets really interesting though.
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  Speaker 1: You can have the leanest code the smartest local AI and the greenest data centers in the world.
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  Speaker 1: But it all operates within human systems, right?
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  Speaker 1: Technology requires rules accountability And above All people to drive The change
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  Speaker 0: which is why the governance landscape Is rapidly shifting Right now from voluntary corporate pledges Demanded to our regulations.
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  Speaker 0: Rebekah Lee Al posted about Singapore's proposed Digital Infrastructure
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  Speaker 1: Act.
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  Speaker 1: This is a major structural
• 12:27
  Speaker 0: shift.
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  Speaker 0: It Is.
• 12:28
  Speaker 0: They are moving from encouraging best practices to enforcing legal standards for power efficiency and service resilience in data centers.
• 12:36
  Speaker 0: If you don't meet the standard, You Don't Operate
• 12:38
  Speaker 1: And that regulatory tightening is happening alongside massive shifts on the legal system itself as Morelda Colombo provided some deep insights into the evolution of net zero litigation.
• 12:49
  Speaker 0: Yeah, we are seeing courts actively shifting the burden of
• 12:52
  Speaker 1: proof.
• 12:52
  Speaker 1: It is no longer enough for a company to just publish a glossy sustainability report with a green claim.
• 12:59
  Speaker 1: Corporations are being held legally accountable for greenwashing and their voluntary commitments are being actively scrutinized under procedural law.
• 13:07
  Speaker 0: The liability's becoming very real And Nils Giesen offered a thought on this.
• 13:12
  Speaker 0: that pushes the boundary even further.
• 13:14
  Speaker 0: He argues that sustainable IT, two point oh needs robust social and governance layer
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  Speaker 1: because it is no longer just an engineering question of how energy efficient our software is
• 13:23
  Speaker 0: exactly.
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  Speaker 0: we have to ask The Governance Question what does This Software actually being used for?
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  Speaker 1: That Is A crucial Point.
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  Speaker 1: Giesen points out that in military and dual-use contexts, a hallucinating AI doesn't just result in a badly written newsletter.
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  Speaker 1: It causes real physical harm.
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  Speaker 1: If we are talking about sustainability in a holistic sense, responsibility and safety have to be part of the development chain.
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  Speaker 1: It cannot just be about carbon!
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  Speaker 1: And
• 13:50
  Speaker 0: if you connect us with that bigger picture... That sense of deep responsibility has been embedded into actual workplace culture.
• 13:57
  Speaker 0: You can't mandate transformation like this from top down and expect it work without team.
• 14:03
  Speaker 0: Drew Wilkinson outlined five key barriers to employee engagement and sustainability.
• 14:08
  Speaker 0: He lists lack of time, lack of education ,lack of place or channels to contribute .
• 14:14
  Speaker 0: Lack of aligning culture and crucially lack of relevance to their specific
• 14:18
  Speaker 1: role.
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  Speaker 1: because if sustainability feels like extra work bolted onto a developer's day job that transformation stalls entirely.
• 14:24
  Speaker 0: you have to activate the ninety-nine percent employees who don't.
• 14:29
  Speaker 1: And speaking of the people driving this transformation, Dr.
• 14:33
  Speaker 1: Katya Shavan shared an incredible piece of historical context that we all need to hear.
• 14:38
  Speaker 1: She reminded us women have been a hidden backbone for IT from the very beginning
• 14:43
  Speaker 0: From Ada Lovelace To The Women Serving As Human Computers In World War II all
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  Speaker 1: the way to modern CIOs and chief sustainability officers.
• 14:51
  Speaker 0: It is a lineage of innovation that often gets completely overlooked.
• 14:55
  Speaker 0: Completely,
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  Speaker 1: Dr.
• 14:56
  Speaker 1: Chabon points out despite facing ongoing structural biases uneven access to venture funding in disproportionately small share overall climate tech investment women are currently at absolute forefront.
• 15:09
  Speaker 1: driving this climate aligned digital transformation.
• 15:12
  Speaker 0: it's powerful reminder.
• 15:13
  Speaker 0: diversity isn't just metric.
• 15:16
  Speaker 0: It directly improves innovation and performance in solving these massive sustainability challenges.
• 15:21
  Speaker 1: The human element truly is the engine, which leads us perfectly into the final area we need to cover—the physical lifecycle of our devices... ...and cold hard math running a climate tech business!
• 15:32
  Speaker 0: Let's shift to hardware life cycle.
• 15:34
  Speaker 1: I really liked Didier Appel's insight on this.
• 15:36
  Speaker 1: He suggested that we reframe the whole concept of IT asset disposition.
• 15:41
  Speaker 1: Even the phrase asset disposition sounds like you were just throwing things into a landfill.
• 15:45
  Speaker 0: Yeah,
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  Speaker 1: he wants to reframe it into circular life cycle services.
• 15:49
  Speaker 1: It is a mindset shift prioritizing refurbishment redeployment and recycling over a linear buy use-and-replace model because
• 15:57
  Speaker 0: changing The wording changes the operational mind set
• 15:59
  Speaker 1: exactly And Brandon Smith shared a massive success story proving that this works in practice.
• 16:05
  Speaker 1: He outlined a partnership between human IT and national grid.
• 16:09
  Speaker 0: I read about that.
• 16:09
  Speaker 1: by collaborating and actually operationalizing circular IT principles, they rocketed their device reuse rates from roughly fifty percent to over ninety percent in a single year.
• 16:20
  Speaker 0: That's incredible progress!
• 16:21
  Speaker 1: It isn't just the theoretical goal that is measurable physical sustainability on this supply chain.
• 16:26
  Speaker 0: This raises an important question though for the businesses and startups actually trying to build these solutions.
• 16:33
  Speaker 0: How do they survive long enough to make an impact?
• 16:36
  Speaker 1: That is a real challenge!
• 16:38
  Speaker 0: Chris Wedding provided his stark reality check, he pointed out that climate tech doesn't die in the pitch deck it dies on the factory floor.
• 16:50
  Speaker 1: Can you clarify that for the listeners who might be more on this software side?
• 16:54
  Speaker 1: What do we mean when say it dies in the unit economics rather than market size.
• 16:59
  Speaker 0: Think of like trying to franchise a new restaurant, It doesn't matter if millions people want your burgers or total addressable markets.
• 17:05
  Speaker 0: If costs five dollars make burger and sell four dollars You lose money every single transaction.
• 17:11
  Speaker 1: That is bad.
• 17:12
  Speaker 1: unit economic
• 17:12
  Speaker 0: Exactly In climate tech are dealing with capex heavy assets.
• 17:18
  Speaker 0: That means massive upfront capital expenditures to build physical infrastructure.
• 17:23
  Speaker 0: When you have long deployment cycles, operational discipline is everything.
• 17:26
  Speaker 1: Process yields installation times
• 17:29
  Speaker 0: warranty reserves These are the metrics that determine survival.
• 17:33
  Speaker 0: as wedding puts it.
• 17:34
  Speaker 0: Operational Discipline Is The New Storytelling.
• 17:37
  Speaker 0: You don't scale a company.
• 17:38
  Speaker 0: use scale processes
• 17:39
  Speaker 1: and if the process isn't profitable at the unit level Scaling it just multiplies the financial damage.
• 17:45
  Speaker 0: Flashy market-sized projections cannot hide sloppy operational
• 17:50
  Speaker 1: math.
• 17:51
  Speaker 1: So what does this all mean for you listening?
• 17:53
  Speaker 1: Over the past two weeks, The conversation across LinkedIn has made it abundantly clear.
• 17:58
  Speaker 1: Sustainability and digital tech have grown up.
• 18:00
  Speaker 0: It really has!
• 18:01
  Speaker 1: It is a core operational engineering & governance discipline Whether its auditing local water strain of an AI data center
• 18:10
  Speaker 0: Choosing compiled language to write leaner code.
• 18:14
  Speaker 1: Navigating the new legal realities of net zero litigation or
• 18:17
  Speaker 0: proving the unit economics of a circular IT supply chain,
• 18:20
  Speaker 1: it is all one deeply integrated ecosystem.
• 18:23
  Speaker 1: if you enjoyed this episode New episodes drop every two weeks.
• 18:27
  Speaker 1: Also check out our other editions on cloud digital products and services artificial intelligence an ICT in tech insights health tech defense Tech.
• 18:35
  Speaker 1: Thank You so much for joining us on this deep dive And don't forget to subscribe So you never miss an update.
• 18:39
  Speaker 0: And before you go, I want to leave you with one final provocative thought to mull over.
• 18:44
  Speaker 0: Drawing on some brilliant insights shared by Karen van der Zanden.
• 18:47
  Speaker 0: We spend so much time in this industry optimizing for the bottom line But are we as a cultured too hyper focus on mere efficiency instead of just being passive consumers?
• 18:59
  Speaker 0: Of these digital tools how can you step up to become a co-architect at The Future Digital Market?
• 19:04
  Speaker 1: That's a great question.
• 19:05
  Speaker 0: How do we build a landscape where sustainability and digital sovereignty carry exactly as much weight in the boardroom, at speed and cost?
• 19:12
  Speaker 0: Something to think about until next time!