Demand Sustainable AI from your Tech and Cloud Providers

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While there has been much speculation about AI being a potential negative force on humanity, what we do know today is that the accelerated use of AI WILL mean an accelerated use of energy. And if that energy source is not renewable, AI will have a meaningful negative impact on CO2 emissions and will accelerate climate change. Even if the energy is renewable, GPUs and CPUs generate significant heat – and if that heat is not captured and used effectively then it too will have a negative impact on warming local environments near data centres.

Balancing Speed and Energy Efficiency

While GPUs use significantly more energy than CPUs, they run many AI algorithms faster than CPUs – so use less energy overall. But the process needs to run – and these are additional processes. Data needs to be discovered, moved, stored, analysed, cleansed. In many cases, algorithms need to be recreated, tweaked and improved. And then that algorithm itself will kick off new digital processes that are often more processor and energy-intensive – as now organisations might have a unique process for every customer or many customer groups, requiring more decisioning and hence more digitally intensive.

The GPUs, servers, storage, cabling, cooling systems, racks, and buildings have to be constructed – often built from raw materials – and these raw materials need to be mined, transported and transformed. With the use of AI exploding at the moment, so is the demand for AI infrastructure – all of which has an impact on the resources of the planet and ultimately on climate change.

Sustainable Sourcing

Some organisations understand this already and are beginning to use sustainable sourcing for their technology services. However, it is not a top priority with Ecosystm research showing only 15% of organisations focus on sustainable procurement.

Top Environmental Sustainability Initiatives

Technology Providers Can Help

Leading technology providers are introducing initiatives that make it easier for organisations to procure sustainable IT solutions. The recently announced HPE GreenLake for Large Language Models will be based in a data centre built and run by Qscale in Canada that is not only sustainably built and sourced, but sits on a grid supplying 99.5% renewable electricity – and waste (warm) air from the data centre and cooling systems is funneled to nearby greenhouses that grow berries. I find the concept remarkable and this is one of the most impressive sustainable data centre stories to date.

The focus on sustainability needs to be universal – across all cloud and AI providers. AI usage IS exploding – and we are just at the tip of the iceberg today. It will continue to grow as it becomes easier to use and deploy, more readily available, and more relevant across all industries and organisations. But we are at a stage of climate warming where we cannot increase our greenhouse gas emissions – and offsetting these emissions just passes the buck.

We need more companies like HPE and Qscale to build this Sustainable Future – and we need to be thinking the same way in our own data centres and putting pressure on our own AI and overall technology value chain to think more sustainably and act in the interests of the planet and future generations. Cloud providers – like AWS – are committed to the NetZero goal (by 2040 in their case) – but this is meaningless if our requirement for computing capacity increases a hundred-fold in that period. Our businesses and our tech partners need to act today. It is time for organisations to demand it from their tech providers to influence change in the industry.

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AI Will be the “Next Big Thing” in End-User Computing

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I have spent many years analysing the mobile and end-user computing markets. Going all the way back to 1995 where I was part of a Desktop PC research team, to running the European wireless and mobile comms practice, to my time at 3 Mobile in Australia and many years after, helping clients with their end-user computing strategies. From the birth of mobile data services (GPRS, WAP, and so on to 3G, 4G and 5G), from simple phones to powerful foldable devices, from desktop computers to a complex array of mobile computing devices to meet the many and varied employee needs. I am always looking for the “next big thing” – and there have been some significant milestones – Palm devices, Blackberries, the iPhone, Android, foldables, wearables, smaller, thinner, faster, more powerful laptops.  

But over the past few years, innovation in this space has tailed off. Outside of the foldable space (which is already four years old), the major benefits of new devices are faster processors, brighter screens, and better cameras. I review a lot of great computers too (like many of the recent Surface devices) – and while they are continuously improving, not much has got my clients or me “excited” over the past few years (outside of some of the very cool accessibility initiatives). 

The Force of AI 

But this is all about to change. Devices are going to get smarter based on their data ecosystem, the cloud, and AI-specific local processing power. To be honest, this has been happening for some time – but most of the “magic” has been invisible to us. It happened when cameras took multiple shots and selected the best one; it happened when pixels were sharpened and images got brighter, better, and more attractive; it happened when digital assistants were called upon to answer questions and provide context.  

Microsoft, among others, are about to make AI smarts more front and centre of the experience – Windows Copilot will add a smart assistant that can not only advise but execute on advice. It will help employees improve their focus and productivity, summarise documents and long chat threads, select music, distribute content to the right audience, and find connections. Added to Microsoft 365 Copilot it will help knowledge workers spend less time searching and reading – and more time doing and improving.  

The greater integration of public and personal data with “intent insights” will also play out on our mobile devices. We are likely to see the emergence of the much-promised “integrated app”– one that can take on many of the tasks that we currently undertake across multiple applications, mobile websites, and sometimes even multiple devices. This will initially be through the use of public LLMs like Bard and ChatGPT, but as more custom, private models emerge they will serve very specific functions. 

Focused AI Chips will Drive New Device Wars 

In parallel to these developments, we expect the emergence of very specific AI processors that are paired to very specific AI capabilities. As local processing power becomes a necessity for some AI algorithms, the broad CPUs – and even the AI-focused ones (like Google’s Tensor Processor) – will need to be complemented by specific chips that serve specific AI functions. These chips will perform the processing more efficiently – preserving the battery and improving the user experience.  

While this will be a longer-term trend, it is likely to significantly change the game for what can be achieved locally on a device – enabling capabilities that are not in the realm of imagination today. They will also spur a new wave of device competition and innovation – with a greater desire to be on the “latest and greatest” devices than we see today! 

So, while the levels of device innovation have flattened, AI-driven software and chipset innovation will see current and future devices enable new levels of employee productivity and consumer capability. The focus in 2023 and beyond needs to be less on the hardware announcements and more on the platforms and tools. End-user computing strategies need to be refreshed with a new perspective around intent and intelligence. The persona-based strategies of the past have to be changed in a world where form factors and processing power are less relevant than outcomes and insights. 

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Cloud Hyperscaler Growth Will Continue into the Foreseeable Future

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All growth must end eventually. But it is a brave person who will predict the end of growth for the public cloud hyperscalers. The hyperscaler cloud revenues have been growing at between 25-60% the past few years (off very different bases – and often including and counting different revenue streams). Even the current softening of economic spend we are seeing across many economies is only causing a slight slowdown. 

Cloud Revenue Patterns of Major Hyperscalers

Looking forward, we expect growth in public cloud infrastructure and platform spend to continue to decline in 2024, but to accelerate in 2025 and 2026 as businesses take advantage of new cloud services and capabilities. However, the sheer size of the market means that we will see slower growth going forward – but we forecast 2026 to see the highest revenue growth of any year since public cloud services were founded. 

The factors driving this growth include: 

  • Acceleration of digital intensity. As countries come out of their economic slowdowns and economic activity increases, so too will digital activity. And greater volumes of digital activity will require an increase in the capacity of cloud environments on which the applications and processes are hosted. 
  • Increased use of AI services. Businesses and AI service providers will need access to GPUs – and eventually, specialised AI chipsets – which will see cloud bills increase significantly. The extra data storage to drive the algorithms – and the increase in CPU required to deliver customised or personalised experiences that these algorithms will direct will also drive increased cloud usage. 
  • Further movement of applications from on-premises to cloud. Many organisations – particularly those in the Asia Pacific region – still have the majority of their applications and tech systems sitting in data centre environments. Over the next few years, more of these applications will move to hyperscalers.  
  • Edge applications moving to the cloud. As the public cloud giants improve their edge computing capabilities – in partnership with hardware providers, telcos, and a broader expansion of their own networks – there will be greater opportunity to move edge applications to public cloud environments. 
  • Increasing number of ISVs hosting on these platforms. The move from on-premise to cloud will drive some growth in hyperscaler revenues and activities – but the ISVs born in the cloud will also drive significant growth. SaaS and PaaS are typically seeing growth above the rates of IaaS – but are also drivers of the growth of cloud infrastructure services. 
  • Improving cloud marketplaces. Continuing on the topic of ISV partners, as the cloud hyperscalers make it easier and faster to find, buy, and integrate new services from their cloud marketplace, the adoption of cloud infrastructure services will continue to grow.  
  • New cloud services. No one has a crystal ball, and few people know what is being developed by Microsoft, AWS, Google, and the other cloud providers. New services will exist in the next few years that aren’t even being considered today. Perhaps Quantum Computing will start to see real business adoption? But these new services will help to drive growth – even if “legacy” cloud service adoption slows down or services are retired. 
Growth in Public Cloud Infrastructure and Platform Revenue

Hybrid Cloud Will Play an Important Role for Many Businesses 

Growth in hyperscalers doesn’t mean that the hybrid cloud will disappear. Many organisations will hit a natural “ceiling” for their public cloud services. Regulations, proximity, cost, volumes of data, and “gravity” will see some applications remain in data centres. However, businesses will want to manage, secure, transform, and modernise these applications at the same rate and use the same tools as their public cloud environments. Therefore, hybrid and private cloud will remain important elements of the overall cloud market. Their success will be the ability to integrate with and support public cloud environments.  

The future of cloud is big – but like all infrastructure and platforms, they are not a goal in themselves. It is what cloud is and will further enable businesses and customers which is exciting. As the rates of digitisation and digital intensity increase, the opportunities for the cloud infrastructure and platform providers will blossom. Sometimes they will be the driver of the growth, and other times they will just be supporting actors. But either way, in 2026 – 20 years after the birth of AWS – the growth in cloud services will be bigger than ever. 

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Ecosystm VendorSphere: Salesforce AI Innovations Transforming CRM ​

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Organisations are moving beyond digitalisation to a focus on building market differentiation. It is widely acknowledged that customer-centric strategies lead to better business outcomes, including increased customer satisfaction, loyalty, competitiveness, growth, and profitability.

AI is the key enabler driving personalisation at scale. It has also become key to improving employee productivity, empowering them to focus on high-value tasks and deepening customer engagements.

Over the last month – at the Salesforce World Tour and over multiple analyst briefings – Salesforce has showcased their desire to solve customer challenges using AI innovations. They have announced a range of new AI innovations across Data Cloud, their integrated CRM platform. ​

Ecosystm Advisors Kaushik Ghatak, Niloy Mukherjee, Peter Carr, and Sash Mukherjee comment on Salesforce’s recent announcements and messaging.

Read on to find out more. ​

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Your Organisation Needs an AI Ethics Policy TODAY!

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It is not hyperbole to state that AI is on the cusp of having significant implications on society, business, economies, governments, individuals, cultures, politics, the arts, manufacturing, customer experience… I think you get the idea! We cannot understate the impact that AI will have on society. In times gone by, businesses tested ideas, new products, or services with small customer segments before they went live. But with AI we are all part of this experiment on the impacts of AI on society – its benefits, use cases, weaknesses, and threats. 

What seemed preposterous just six months ago is not only possible but EASY! Do you want a virtual version of yourself, a friend, your CEO, or your deceased family member? Sure – just feed the data. Will succession planning be more about recording all conversations and interactions with an executive so their avatar can make the decisions when they leave? Why not? How about you turn the thousands of hours of recorded customer conversations with your contact centre team into a virtual contact centre team? Your head of product can present in multiple countries in multiple languages, tailored to the customer segments, industries, geographies, or business needs at the same moment.  

AI has the potential to create digital clones of your employees, it can spread fake news as easily as real news, it can be used for deception as easily as for benefit. Is your organisation prepared for the social, personal, cultural, and emotional impacts of AI? Do you know how AI will evolve in your organisation?  

When we focus on the future of AI, we often interview AI leaders, business leaders, futurists, and analysts. I haven’t seen enough focus on psychologists, sociologists, historians, academics, counselors, or even regulators! The Internet and social media changed the world more than we ever imagined – at this stage, it looks like these two were just a rehearsal for the real show – Artificial Intelligence. 

Lack of Government or Industry Regulation Means You Need to Self-Regulate 

These rapid developments – and the notable silence from governments, lawmakers, and regulators – make the requirement for an AI Ethics Policy for your organisation urgent! Even if you have one, it probably needs updating, as the scenarios that AI can operate within are growing and changing literally every day.  

  • For example, your customer service team might want to create a virtual customer service agent from a real person. What is the policy on this? How will it impact the person? 
  • Your marketing team might be using ChatGPT or Bard for content creation. Do you have a policy specifically for the creation and use of content using assets your business does not own?  
  • What data is acceptable to be ingested by a public Large Language Model (LLM). Are are you governing data at creation and publishing to ensure these policies are met?  
  • With the impending public launch of Microsoft’s Co-Pilot AI service, what data can be ingested by Co-Pilot? How are you governing the distribution of the insights that come out of that capability? 

If policies are not put in place, data tagged, staff trained, before using a tool such as Co-Pilot, your business will be likely to break some privacy or employment laws – on the very first day! 

What do the LLMs Say About AI Ethics Policies? 

So where do you go when looking for an AI Ethics policy? ChatGPT and Bard of course! I asked the two for a modern AI Ethics policy. 

You can read what they generated in the graphic below.

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I personally prefer the ChatGPT4 version as it is more prescriptive. At the same time, I would argue that MOST of the AI tools that your business has access to today don’t meet all of these principles. And while they are tools and the ethics should dictate the way the tools are used, with AI you cannot always separate the process and outcome from the tool.  

For example, a tool that is inherently designed to learn an employee’s character, style, or mannerisms cannot be unbiased if it is based on a biased opinion (and humans have biases!).  

LLMs take data, content, and insights created by others, and give it to their customers to reuse. Are you happy with your website being used as a tool to train a startup on the opportunities in the markets and customers you serve?  

By making content public, you acknowledge the risk of others using it. But at least they visited your website or app to consume it. Not anymore… 

A Policy is Useless if it Sits on a Shelf 

Your AI ethics policy needs to be more than a published document. It should be the beginning of a conversation across the entire organisation about the use of AI. Your employees need to be trained in the policy. It needs to be part of the culture of the business – particularly as low and no-code capabilities push these AI tools, practices, and capabilities into the hands of many of your employees.  

Nearly every business leader I interview mentions that their organisation is an “intelligent, data-led, business.” What is the role of AI in driving this intelligent business? If being data-driven and analytical is in the DNA of your organisation, soon AI will also be at the heart of your business. You might think you can delay your investments to get it right – but your competitors may be ahead of you.  

So, as you jump head-first into the AI pool, start to create, improve and/or socialise your AI Ethics Policy. It should guide your investments, protect your brand, empower your employees, and keep your business resilient and compliant with legacy and new legislation and regulations. 

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The Future of the Digital Enterprise – India

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Organisations have had to transform and innovate to survive over the last two years. However, now when they look at their competitors, they see that everyone has innovated at about the same pace. The 7-year innovation cycle is history in today’s world – organisations need the right strategy and technologies to bring the time to market for innovations down to 1-2 years.

As they continue to innovate to stay ahead of the competition, here are 5 things organisations in India should keep in mind:

  • The drivers of innovation will shift rapidly and industry trends need to be monitored continually to adapt to these shifts.
  • Their biggest challenge in deploying Data & AI solutions will be identification of the right data for the right purpose – this will require a robust data architecture.
  • While customer experience gives them immediate and tangible benefits, employee experience is almost equally – if not more – important.
  • Cloud investments have helped build distributed enterprises – but streamlining investments needs a lot of focus now.
  • There is a misalignment between organisations’ overall awareness of growing cyber threats and risks and their responses to them. A new cyber approach is urgently needed.

More insights into the India tech market are below.

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The Future of the Digital Enterprise – Southeast Asia

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Southeast Asia has evolved into an innovation hub with Singapore at the centre. The entrepreneurial and startup ecosystem has grown significantly across the region – for example, Indonesia now has the 5th largest number of startups in the world.  

Organisations in the region are demonstrating a strong desire for tech-led innovation, innovation in experience delivery, and in evolving their business models to bring innovative products and services to market.    

Here are 5 insights on the patterns of technology adoption in Southeast Asia, based on the findings of the Ecosystm Digital Enterprise Study, 2022.

  • Data and AI investments are closely linked to business outcomes. There is a clear alignment between technology and business.
  • Technology teams want better control of their infrastructure. Technology modernisation also focuses on data centre consolidation and cloud strategy
  • Organisations are opting for a hybrid multicloud approach. They are not necessarily doing away with a ‘cloud first’ approach – but they have become more agnostic to where data is hosted.
  • Cybersecurity underpins tech investments. Many organisations in the region do not have the maturity to handle the evolving threat landscape – and they are aware of it. 
  • Sustainability is an emerging focus area. While more effort needs to go in to formalise these initiatives, organisations are responding to market drivers.

More insights into the Southeast Asia tech market below.

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