The 28th United Nations Climate Change Conference (or COP28) took place at the end of 2023 in one of the most climate-vulnerable countries in the world – the UAE. The event brought together nations, leaders, and climate experts to unite around tangible climate action and deliver realistic solutions.
COP28 marked a watershed moment in the global effort to fight climate change because it concluded the first Global Stocktake – a routine assessment of progress under the Paris Agreement that occurs every five years. It is clear that we are not on track to meet the agreement’s goals, but the decisions and actions taken during COP28 can redefine the trajectory of climate action.
COP27: Laying the Foundation
COP27 laid the groundwork for this year’s conference. The summit focused on mitigation, adaptation, finance, and collaboration. The key outcomes of COP27 included the creation of the loss and damage fund, new pledges to the Adaptation Fund, and advancements in the Santiago Network focused on technical support for climate-affected regions. The conference also saw progress on the Global Stocktake and formal recognition of new issues such as water, food security, and forests within climate deliberations.
However, there was widespread criticism for failing to live up to the urgency of impending climate crisis. Despite being called the “implementation COP”, nothing decisive was done to ensure global warming is limited to 1.5 degrees celsius.
COP28: Milestones
Launching the first-ever Global Stocktake. The Global Stocktake was the spotlight of this year’s event and covered various climate issues, including energy, transport, and nature. Despite strong opposition from Oil & Gas interests, negotiators secured an agreement indicating the start of the end of the fossil fuel era – a much-needed conclusion to the hottest year in history. The next global assessment of Paris Agreement targets is expected to take place at COP33 in 2028.
Supporting sustainable agriculture. A landmark declaration on sustainable agriculture was adopted to address climate-related threats to global food systems. Signed by 160 countries, the declaration pledged a collective commitment by participating nations to expedite the integration of agriculture and food systems into national climate actions by 2025. For the first time ever, the summit also featured an entire day devoted to food and agriculture and saw a food systems roadmap laid out by the Food and Agriculture Organisation (FAO).
Operationalising the “Loss and Damage” fund. The conference saw the approval of the “loss and damage fund” that was first tabled at COP27 last year. The fund has been a long-requested support for developing nations facing the impact of climate change.
Tripling renewables and doubling energy efficiency by 2030. 118 countries signed a renewable energy pledge to triple the world’s green energy capacity to 11,000 GW by 2030, reducing the reliance on fossil fuels in generating energy. The pledge is expected to see global average annual rate of energy efficiency improvements from around 2% to over 4% every year until 2030. While the pledge spearheaded by the EU, the US, and the UAE is not legally binding, it is a step in the right direction.
Adapting to a warmer world. COP28 provided a framework for the ‘Global Goal on Adaptation’ to guide countries in their efforts to protect their people and ecosystems from climate change. An explicit 2030 date has been integrated into the text for targets on water security, ecosystem restoration, health, climate-resilient food systems, resilient human settlements, reduction of poverty, and protection of tangible cultural heritage.
Addressing methane. Methane took centre stage at COP28, reflecting its significant role in current global warming. US, Canada, Brazil, and Egypt announced more than USD 1 billion in funding to reduce methane emissions. Despite facing political challenges, these measures signify a shift towards concrete regulatory and pricing tools, marking a step forward in addressing methane’s impact on climate protection.
How COP28 Could Have Been More Impactful
Better funding allocations. Although the “loss and damage” funding agreement seems like a major outcome, the actual financial commitments fell far short. US and China, despite being the world’s largest emitters, extended only USD 17.5 million and USD 10 million to the fund, respectively. There is also debate about how funds should be distributed, with mature countries favouring aid allocation based on vulnerability. This approach might exclude middle-income countries that have suffered significant climate-related damage recently.
More focus on AI. While COP28 tackled critical climate issues, it overlooked a significant concern – the environmental impact of AI. While AI holds promise for improved sustainability, it is important to address the environmental consequences of AI model training and deployment. The absence of scrutiny on the ecological impact of AI represents a missed early opportunity, considering the widespread hype and significant investments in the technology.
Recognising climate refugees. The increase in climate-related displacement is a growing concern, with millions already affected and predictions of a significant rise by 2050. International law does not recognise those displaced by climate events as refugees. Despite this, the topic wasn’t adequately explored at COP28, highlighting the need for inclusive discussions and solutions for safe migration pathways.
A Call for Unified Action
While COP28 and similar forums highlight the severity of the climate crisis, the real power lies in continuous collective conversations that identify gaps, strive to bridge them, and drive meaningful change. Ecosystm, in collaboration with partners Kyndryl and Microsoft, conducted a Global Sustainability Barometer study, that reveals that while 85% of global organisations acknowledge the strategic importance of sustainability goals, only 16% have successfully integrated sustainability into their corporate and transformation strategies with tangible data.
While governments and policy makers continue to focus on building a sustainable future for the planet, this is time for a shift in mindset and action is pivotal for a unified global effort in addressing climate challenges and building a sustainable future – from organisations and individuals alike.
Earlier in the year, Microsoft unveiled its vision for Copilot, a digital companion that aims to provide a unified user experience across Bing, Edge, Microsoft 365, and Windows. This vision includes a consistent user experience. The rollout began with Windows in September and expanded to Microsoft 365 Copilot for enterprise customers this month.
Many organisations across Asia Pacific will soon face the question on whether to invest in Microsoft 365 Copilot – despite its current limitations in supporting all regional languages. Copilot is currently supported in English (US, GB, AU, CA, IN), Japanese, and Chinese Simplified. Microsoft plans to support more languages such as Arabic, Chinese Traditional, Korean and Thai over the first half of 2024. There are still several languages used across Asia Pacific that will not be supported until at least the second half of 2024 or later.
Access to Microsoft 365 Copilot comes with certain prerequisites. Organisations need to have either a Microsoft 365 E3 or E5 license and an Azure Active Directory account. F3 licenses do not currently have access to 365 Copilot. For E3 license holders the cost per user for adding Copilot would nearly double – so it is a significant extra spend and will need to deliver measurable and tangible benefits and a strong business case. It is doubtful whether most organisations will be able to justify this extra spend.
However, Copilot has the potential to significantly enhance the productivity of knowledge workers, saving them many hours each week, with hundreds of use cases already emerging for different industries and user profiles. Microsoft is offering a plethora of information on how to best adopt, deploy, and use Copilot. The key focus when building a business case should revolve around how knowledge workers will use this extra time.
Maximising Copilot Integration: Steps to Drive Adoption and Enhance Productivity
Identifying use cases, building the business proposal, and securing funding for Copilot is only half the battle. Driving the change and ensuring all relevant employees use the new processes will be significantly harder. Consider how employees currently use their productivity tools compared to 15 years ago, with many still relying on the same features and capabilities in their Office suites as they did in earlier versions. In cases where new features were embraced, it typically occurred because knowledge workers didn’t have to make any additional efforts to incorporate them, such as the auto-type ahead functions in email or the seamless integration of Teams calls.
The ability of your organisation to seamlessly integrate Copilot into daily workflows, optimising productivity and efficiency while harnessing AI-generated data and insights for decision-making will be of paramount importance. It will be equally important to be watchful to mitigate potential risks associated with an over-reliance on AI without sufficient oversight.
Implementing Copilot will require some essential steps:
- Training and onboarding. Provide comprehensive training to employees on how to use Copilot’s features within Microsoft 365 applications.
- Integration into daily tasks. Encourage employees to use Copilot for drafting emails, documents, and generating meeting notes to familiarise them with its capabilities.
- Customisation. Tailor Copilot’s settings and suggestions to align with company-specific needs and workflows.
- Automation. Create bots, templates, integrations, and other automation functions for multiple use cases. For example, when users first log onto their PC, they could get a summary of missed emails, chats – without the need to request it.
- Feedback loop. Implement a feedback mechanism to monitor how Copilot is used and to make adjustments based on user experiences.
- Evaluating effectiveness. Gauge how Copilot’s features are enhancing productivity regularly and adjust usage strategies accordingly. Focus on the increased productivity – what knowledge workers now achieve with the time made available by Copilot.
Changing the behaviours of knowledge workers can be challenging – particularly for basic processes that they have been using for years or even decades. Knowledge of use cases and opportunities for Copilot will not just filter across the organisation. Implementing formal training and educational programs and backing them up with refresher courses is important to ensure compliance and productivity gains.
The challenge of AI is that it is hard to build a business case when the outcomes are inherently uncertain. Unlike a traditional process improvement procedure, there are few guarantees that AI will solve the problem it is meant to solve. Organisations that have been experimenting with AI for some time are aware of this, and have begun to formalise their Proof of Concept (PoC) process to make it easily repeatable by anyone in the organisation who has a use case for AI. PoCs can validate assumptions, demonstrate the feasibility of an idea, and rally stakeholders behind the project.
PoCs are particularly useful at a time when AI is experiencing both heightened visibility and increased scrutiny. Boards, senior management, risk, legal and cybersecurity professionals are all scrutinising AI initiatives more closely to ensure they do not put the organisation at risk of breaking laws and regulations or damaging customer or supplier relationships.
13 Steps to Building an AI PoC
Despite seeming to be lightweight and easy to implement, a good PoC is actually methodologically sound and consistent in its approach. To implement a PoC for AI initiatives, organisations need to:
- Clearly define the problem. Businesses need to understand and clearly articulate the problem they want AI to solve. Is it about improving customer service, automating manual processes, enhancing product recommendations, or predicting machinery failure?
- Set clear objectives. What will success look like for the PoC? Is it about demonstrating technical feasibility, showing business value, or both? Set tangible metrics to evaluate the success of the PoC.
- Limit the scope. PoCs should be time-bound and narrow in scope. Instead of trying to tackle a broad problem, focus on a specific use case or a subset of data.
- Choose the right data. AI is heavily dependent on data. For a PoC, select a representative dataset that’s large enough to provide meaningful results but manageable within the constraints of the PoC.
- Build a multidisciplinary team. Involve team members from IT, data science, business units, and other relevant stakeholders. Their combined perspectives will ensure both technical and business feasibility.
- Prioritise speed over perfection. Use available tools and platforms to expedite the development process. It’s more important to quickly test assumptions than to build a highly polished solution.
- Document assumptions and limitations. Clearly state any assumptions made during the PoC, as well as known limitations. This helps set expectations and can guide future work.
- Present results clearly. Once the PoC is complete, create a clear and concise report or presentation that showcases the results, methodologies, and potential implications for the business.
- Get feedback. Allow stakeholders to provide feedback on the PoC. This includes end-users, technical teams, and business leaders. Their insights will help refine the approach and guide future iterations.
- Plan for the next steps. What actions need to follow a successful PoC demonstration? This might involve a pilot project with a larger scope, integrating the AI solution into existing systems, or scaling the solution across the organisation.
- Assess costs and ROI. Evaluate the costs associated with scaling the solution and compare it with the anticipated ROI. This will be crucial for securing budget and support for further expansion.
- Continually learn and iterate. AI is an evolving field. Use the PoC as a learning experience and be prepared to continually iterate on your solutions as technologies and business needs evolve.
- Consider ethical and social implications. Ensure that the AI initiative respects privacy, reduces bias, and upholds the ethical standards of the organisation. This is critical for building trust and ensuring long-term success.
Customising AI for Your Business
The primary purpose of a PoC is to validate an idea quickly and with minimal risk. It should provide a clear path for decision-makers to either proceed with a more comprehensive implementation or to pivot and explore alternative solutions. It is important for the legal, risk and cybersecurity teams to be aware of the outcomes and support further implementation.
AI initiatives will inevitably drive significant productivity and customer experience improvements – but not every solution will be right for the business. At Ecosystm, we have come across organisations that have employed conversational AI in their contact centres to achieve entirely distinct results – so the AI experience of peers and competitors may not be relevant. A consistent PoC process that trains business and technology teams across the organisation and encourages experimentation at every possible opportunity, would be far more useful.
Ecosystm research reveals a stark reality: 75% of technology leaders in Financial Services anticipate data breaches.
Given the sector’s regulatory environment, data breaches carry substantial financial implications, emphasising the critical importance of giving precedence to cybersecurity. This is compelling a fresh cyber strategy focused on early threat detection and reduction of attack impact.
Read on to find out how tech leaders are building a culture of cyber-resilience, re-evaluating their cyber policies, and adopting technologies that keep them one step ahead of their adversaries.
Download ‘Cyber-Resilience in Finance: People, Policy & Technology’ as a PDF
The impact of AI on Customer Experience (CX) has been profound and continues to expand. AI allows a a range of advantages, including improved operational efficiency, cost savings, and enhanced experiences for both customers and employees.
AI-powered solutions have the capability to analyse vast volumes of customer data in real-time, providing organisations with invaluable insights into individual preferences and behaviour. When executed effectively, the ability to capture, analyse, and leverage customer data at scale gives organisations significant competitive edge. Most importantly, AI unlocks opportunities for innovation.
Read on to discover the transformative impact of AI on customer experiences.
Click here to download ‘Customer Experience Redefined: The Role of AI’ as a PDF
Generative AI has stolen the limelight in 2023 from nearly every other technology – and for good reason. The advances made by Generative AI providers have been incredible, with many human “thinking” processes now in line to be automated.
But before we had Generative AI, there was the run-of-the-mill “traditional AI”. However, despite the traditional tag, these capabilities have a long way to run within your organisation. In fact, they are often easier to implement, have less risk (and more predictability) and are easier to generate business cases for. Traditional AI systems are often already embedded in many applications, systems, and processes, and can easily be purchased as-a-service from many providers.
Unlocking the Potential of AI Across Industries
Many organisations around the world are exploring AI solutions today, and the opportunities for improvement are significant:
- Manufacturers are designing, developing and testing in digital environments, relying on AI to predict product responses to stress and environments. In the future, Generative AI will be called upon to suggest improvements.
- Retailers are using AI to monitor customer behaviours and predict next steps. Algorithms are being used to drive the best outcome for the customer and the retailer, based on previous behaviours and trained outcomes.
- Transport and logistics businesses are using AI to minimise fuel usage and driver expenses while maximising delivery loads. Smart route planning and scheduling is ensuring timely deliveries while reducing costs and saving on vehicle maintenance.
- Warehouses are enhancing the safety of their environments and efficiently moving goods with AI. Through a combination of video analytics, connected IoT devices, and logistical software, they are maximising the potential of their limited space.
- Public infrastructure providers (such as shopping centres, public transport providers etc) are using AI to monitor public safety. Video analytics and sensors is helping safety and security teams take public safety beyond traditional human monitoring.
AI Impacts Multiple Roles
Even within the organisation, different lines of business expect different outcomes for AI implementations.
- IT teams are monitoring infrastructure, applications, and transactions – to better understand root-cause analysis and predict upcoming failures – using AI. In fact, AIOps, one of the fastest-growing areas of AI, yields substantial productivity gains for tech teams and boosts reliability for both customers and employees.
- Finance teams are leveraging AI to understand customer payment patterns and automate the issuance of invoices and reminders, a capability increasingly being integrated into modern finance systems.
- Sales teams are using AI to discover the best prospects to target and what offers they are most likely to respond to.
- Contact centres are monitoring calls, automating suggestions, summarising records, and scheduling follow-up actions through conversational AI. This is allowing to get agents up to speed in a shorter period, ensuring greater customer satisfaction and increased brand loyalty.
Transitioning from Low-Risk to AI-Infused Growth
These are just a tiny selection of the opportunities for AI. And few of these need testing or business cases – many of these capabilities are available out-of-the-box or out of the cloud. They don’t need deep analysis by risk, legal, or cybersecurity teams. They just need a champion to make the call and switch them on.
One potential downside of Generative AI is that it is drawing unwarranted attention to well-established, low-risk AI applications. Many of these do not require much time from data scientists – and if they do, the challenge is often finding the data and creating the algorithm. Humans can typically understand the logic and rules that the models create – unlike Generative AI, where the outcome cannot be reverse-engineered.
The opportunity today is to take advantage of the attention that LLMs and other Generative AI engines are getting to incorporate AI into every conceivable aspect of a business. When organisations understand the opportunities for productivity improvements, speed enhancement, better customer outcomes and improved business performance, the spend on AI capabilities will skyrocket. Ecosystm estimates that for most organisations, AI spend will be less than 5% of their total tech spend in 2024 – but it is likely to grow to over 20% within the next 4-5 years.
It seems for many employees, the benefits of working from home or even adopting a hybrid model are a thing of the past. Employees are returning to the grind of long commutes and losing hours in transit. What is driving this shift in sentiment? CEOs, who once rooted for remote work, have undergone a change of heart – many say that remote work hampers their ability to innovate.
That may not be the real reason, however. There is a good chance that the CEO and/or other managers feel they have lost control or visibility over their employees. Returning to a more traditional management approach, where everyone is within direct sight, might seem like a simpler solution.
The Myths of Workplace Innovation
I find it ironic that organisations say they want employees to come into the office because they cannot innovate at the same rate. What the last few years have demonstrated – and quite conclusively – is that employees can innovate wherever they are, if they are driven to it and have the right tools. So, organisations need to evaluate whether they have innovated on and evolved their hybrid and remote work solutions effectively, to continue to support hybrid work – and innovation.
What is confusing about this stance that many organisations are taking, is that when an organisation has multiple offices, they are effectively a hybrid business – they have had people working from different locations, but have never felt the need to get all their staff together for 3-5 days every week for organisation-wide innovation that is suddenly so important today.
The CEO of a tech research firm once said – the office used to be considered the place to get together to use the tools we need to innovate; but the reality is that the office is just one of the tools that businesses have, to drive their organisation forward. Ironically, this same CEO has recently called everyone back into the office 3 days a week!
Is Remote Work the Next Step in Employee Rights?
It has become clear that remote and hybrid work is the next step in employees getting greater rights. Many organisations fought against the five-day work weeks, claiming they wouldn’t make as much money as they did when employees worked whenever they were told. They fought against the 40-hour work week (in France some fought against the 35-hour work week!) They fight against the introduction of new public holidays, against increases to the minimum wages, against paid parental leave.
Some industries, companies, unions, and countries are looking to (or already have) formalised hybrid and remote work in their policies and regulations. More unions and businesses will do this – and employees will have choice.
People will have the option to work for an employer who wants their employees to come into the office – or work for someone else. And this will depend on preferences and working styles – some employees enjoy the time spent away from home and like the social nature of office environments. But many also like the extra time, money, and flexibility that remote work allows.
There might be many reasons why leadership teams would want employees to come into the office – and establishing and maintaining a common corporate culture would be a leading reason. But what they need to do is stop pretending it is about “innovation”. Innovation is possible while working remotely, as it is when working from separate offices or even different floors within the same building.
Evolving Employee Experience & Collaboration Needs
Organisations today face a challenge – and it is not the inability to innovate in a hybrid work environment! It is in their ability to deliver the employee experience that their employees want. This is more challenging now because there are more preferences, options, and technologies available. But it is established that organisations need to continue to evolve their employee experience.
Technology does and will continue to play an important role in keeping our employees connected and productive. AI – such as Microsoft Copilot – will continue to improve our productivity. But the management needs to evolve with the technology. If the senior management feels that connecting people will help to solve the current growth challenges in the business, then it becomes the role of managers to better connect people – not just teams in offices, but virtual teams across the entire organisation.
Organisations that have focused their energies on connecting their employees better, regardless of their location (such as REA in Australia), find that productivity and innovation rates are better than when people are physically together. What do they do differently?
- Managers find their roles have moved from supporting individual employees to connecting employees
- Documentation of progress and challenges means that everyone knows where to focus their energies
- Managed virtual (and in-person) meetings mean that everyone has a voice and gets to contribute (not the loudest, most talkative or most senior person)
Remote and hybrid workers are often well-positioned to come up with new and innovative ideas. Senior management can encourage innovation and risk-taking by creating a safe environment for employees to share their ideas and by providing them with the resources they need to develop and implement their ideas. Sometimes these resources are in an office – but they don’t have to be. Manufacturers are quickly moving to complete digital development, prototyping, and testing of their new and improved products and services. Digital is often faster, better, and more innovative than physical – but employees need to be allowed to embrace these new platforms and tools to drive better organisational and customer outcomes.
What the pandemic has taught us is that people are good at solving problems; they are good at innovating irrespective of whether their managers are watching or not.
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.
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.
Technology has been reshaping the Real Estate industry landscape. Advancements in manufacturing technologies, digital tools, AI & analytics, and IoT – coupled with customer and employee expectations – are revolutionising how properties are built, bought, sold, managed, and experienced.
The evolution of RealTech and PropTech has a far-reaching impact on the industry, streamlining processes, improving customer experiences, and driving innovation across the entire sector.
Read on to find out how technology impacts the entire value chain; the key drivers of Real Estate evolution; the strong influence of “smart consumers”; and what Ecosystm VP Industry Insights Sash Mukherjee thinks where the industry is headed.
Download ‘The Future of Real Estate’ as a PDF