Transforming-Public-Sector-Processes-A-Roadmap-to-Unlocking-Efficiency
Transforming Public Sector Processes: A Roadmap to Unlocking Efficiency

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We spoke about what public sector agencies should consider when building citizen-centric services. Integrating technology into organisational processes requires a similarly strategic approach that considers immediate needs, emerging enablers, and futuristic innovations.

Here is a comprehensive look at what public sector organisations should consider when integrating technology into processes.

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Click here to download ‘Transforming Public Sector Processes: A Roadmap to Unlocking Efficiency’ as a PDF.

1. Process Essentials: Laying the Groundwork

The immediate view focuses on deploying technologies that are widely adopted and essential for current digital service provision. These foundational technologies serve as the backbone for enhancing process efficiency.

  • Code. At the most basic level, the foundation is built on code – the programming languages and frameworks used to create digital services. This includes technologies like HTML, CSS, JavaScript, Java, Python, etc. A typical approach is to have a front-end web layer for the user interface and a back-end application layer for processing.
  • Monolithic ERP. These systems are also crucial, especially in the early stages. These integrated software suites help manage core functions like customer management and document handling. They provide comprehensive, pre-built solutions that can be customised to specific needs. ERPs enable organisations to effectively manage complex processes from the start.

2. Emerging Catalysts: Accelerating Processes

As organisations establish foundational technologies, they should look towards second-generation enablers. Although less mature, these technologies offer emerging digital opportunities, and can significantly enhance service differentiation, through improved processes.

  • PaaS. As digital services mature, organisations can leverage platform-as-a-service (PaaS) solutions hosted in the cloud. PaaS provides greater scalability, flexibility, and reduced infrastructure management overhead compared to custom development approaches. Adopting a microservices architecture on PaaS allows for developing independent components that can be updated independently, promoting continuous improvement. This modern, modular approach is highly efficient.
  • Low Code/ No Code. LC/NC platforms further simplify application development by providing intuitive, visual tools that don’t require extensive coding expertise. They build on PaaS capabilities while minimising the need for deep technical skills. These environments also facilitate collaboration by enabling partners and third-parties to easily create custom solutions that integrate with the organisation’s systems. This spurs innovation through an ecosystem of complementary apps and services.

3. Future-Forward Capabilities: Next-Gen Processes

The futuristic view focuses on forward-looking technologies that address long-term roadblocks and offer transformative potential. These technologies are currently speculative but hold the promise of significantly reshaping the market.

  • Complex RPA and ML. Robotic process automation (RPA) and machine learning take technological maturity to the next level by automating routine tasks and optimising decision-making through intelligent algorithms. The integration of RPA with machine learning goes beyond simple automation to enable more complex, data-driven decision processes across the workflow. Analysts predict that by 2025, up to 50% of work could be automated this way, drastically improving efficiency.
  • Enterprise-Wide Microservices Architecture. An enterprise-wide microservices architecture represents an advanced approach suitable for collaboration between agencies, technical service providers, and partners. Each microservice is designed to be independently deployable, testable, and focused on specific capabilities. This decentralised model allows services to be updated or replaced without disrupting the entire system, enhancing resilience. On a PaaS platform, it enables an agile, scalable approach aligned with modern e-government needs.
  • Industry Cloud. The Industry Cloud is essentially a highly configurable PaaS solution, designed to meet the specific needs of not just one government agency or jurisdiction, but with adaptability for broader use.

Ecosystm Opinion

A comprehensive roadmap should outline how to build upon current process foundations with emerging catalysts like cloud platforms and low-code development, while actively preparing for future-forward capabilities around automation, microservices architectures, and industry cloud solutions.

By taking a long-term, systematic approach to integrating technology at every stage of the process lifecycle, agencies can cultivate an adaptable digital process ecosystem that continually evolves in lockstep with technological innovation. The goal is to foster processes that don’t just endure disruption, but fundamentally improve because of it – cementing organisational resilience and agility for decades to come.

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Transforming Data Centres: Equinix’s Platform and Service Integration

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As AI evolves, the supporting infrastructure has become a crucial consideration for organisations and technology companies alike. AI demands massive processing power and efficient data handling, making high-performance computing clusters and advanced data management systems essential. Scalability, efficiency, security, and reliability are key to ensuring AI systems handle increasing demands and sensitive data responsibly.

Data centres must evolve to meet the increasing demands of AI and growing data requirements.

Equinix recently hosted technology analysts at their offices and data centre facilities in Singapore and Sydney to showcase how they are evolving to maintain their leadership in the colocation and interconnection space.

Equinix is expanding in Latin America, Africa, the Middle East, and Asia Pacific. In Asia Pacific, they recently opened data centres in Kuala Lumpur and Johor Bahru, with capacity additions in Mumbai, Sydney, Melbourne, Tokyo, and Seoul. Plans for the next 12 months include expanding in existing cities and entering new ones, such as Chennai and Jakarta.

Ecosystm analysts comment on Equinix’s growth potential and opportunities in Asia Pacific.

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Click here to download ‘Transforming Data Centres: Equinix’s Platform and Service Integration’ as a PDF

Small Details, Big Impact

TIM SHEEDY. The tour of the new Equinix data centre in Sydney revealed the complexity of modern facilities. For instance, the liquid cooling system, essential for new Nvidia chipsets, includes backup cold water tanks for redundancy. Every system and process is designed with built-in redundancy.

As power needs grow, so do operational and capital costs. The diesel generators at the data centre, comparable to a small power plant, are supported by multiple fuel suppliers from several regions in Sydney to ensure reliability during disasters.

Security is critical, with some areas surrounded by concrete walls extending from the ceiling to the floor, even restricting access to Equinix staff.

By focusing on these details, Equinix enables customers to quickly set up and manage their environments through a self-service portal, delivering a cloud-like experience for on-premises solutions.

Equinix’s Commitment to the Environment

ACHIM GRANZEN. Compute-intensive AI applications challenge data centres’ “100% green energy” pledges, prompting providers to seek additional green measures. Equinix addresses this through sustainable design and green energy investments, including liquid cooling and improved traditional cooling. In Singapore, one of Equinix’s top 3 hubs, the company partnered with the government and Sembcorp to procure solar power from panels on public buildings. This improves Equinix’s power mix and supports Singapore’s renewable energy sector.

TIM SHEEDY Building and operating data centres sustainably is challenging. While the basics – real estate, cooling, and communications – remain, adding proximity to clients, affordability, and 100% renewable energy complicates matters. In Australia, reliant on a mixed-energy grid, Equinix has secured 151 MW of renewable energy from Victoria’s Golden Plains Wind Farm, aiming for 100% renewable by 2029.

Equinix leads with AIA-rated data centres that operate in warmer conditions, reducing cooling needs and boosting energy efficiency. Focusing on efficient buildings, sustainable water management, and a circular economy, Equinix aims for climate neutrality by 2030, demonstrating strong environmental responsibility.

Equinix’s Private AI Value Proposition

ACHIM GRANZEN. Most AI efforts, especially GenAI, have occurred in the public cloud, but there’s rising demand for Private AI due to concerns about data availability, privacy, governance, cost, and location. Technology providers in a position to offer alternative AI stacks (usually built on top of a GPU-as-a-service model) to the hyperscalers find themselves in high interest. Equinix, in partnership with providers such as Nvidia, offers Private AI solutions on a global turnkey AI infrastructure. These solutions are ideal for industries with large-scale operations and connectivity challenges, such as Manufacturing, or those slow to adopt public cloud.

SASH MUKHERJEE. Equinix’s Private AI value proposition will appeal to many organisations, especially as discussions on AI cost efficiency and ROI evolve. AI unites IT and business teams, and Equinix understands the need for conversations at multiple levels. Infrastructure leaders focus on data strategy capacity planning; CISOs on networking and security; business lines on application performance, and the C-suite on revenue, risk, and cost considerations. Each has a stake in the AI strategy. For success, Equinix must reshape its go-to-market message to be industry-specific (that’s how AI conversations are shaping) and reskill its salesforce for broader conversations beyond infrastructure.

Equinix’s Growth Potential

ACHIM GRANZEN. In Southeast Asia, Malaysia and Indonesia provide growth opportunities for Equinix. Indonesia holds massive potential as a digital-savvy G20 country. In Malaysia, the company’s data centres can play a vital part in the ongoing Mydigital initiative, having a presence in the country before the hyperscalers. Also, the proximity of the Johor Bahru data centre to Singapore opens additional business opportunities.

TIM SHEEDY. Equinix is evolving beyond being just a data centre real estate provider. By developing their own platforms and services, along with partner-provided solutions, they enable customers to optimise application placement, manage smaller points of presence, enhance cloud interconnectivity, move data closer to hyperscalers for backup and performance, and provide multi-cloud networking. Composable services – such as cloud routers, load balancers, internet access, bare metal, virtual machines, and virtual routing and forwarding – allow seamless integration with partner solutions.

Equinix’s focus over the last 12 months on automating and simplifying the data centre management and interconnection services is certainly paying dividends, and revenue is expected to grow above tech market growth rates.

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Future-Proofing Citizen Services: Technology Strategies for the Public Sector

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Innovation is a driving force behind new approaches, often occurring at the point of adoption rather than technology development. As public sector organisations increasingly focus on improving citizen services through technology, it is important to adopt a strategic approach that considers innovation as a complex journey of systemic and cultural transformation. This strategic approach should guide the integration of technology into citizen services.

Here is a comprehensive look at what public sector organisations should consider when integrating technology into citizen services.

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Download ‘Future-Proofing Citizen Services: Technology Strategies for the Public Sector‘ as a PDF

1. Immediate View: Foundational Technologies

The immediate view focuses on deploying technologies that are widely adopted and essential for current digital service provision. These foundational technologies serve as the backbone for enhancing citizen services.

Foundational Technologies

Web 2.0. Establishing a solid online presence is usually the first step, as it is the broadest channel for reaching customers. Web 2.0 refers to the current state of the internet, encompassing dynamic content and interactive websites.

Mobile Applications. Given that mobile usage has surpassed desktop, a mobile-responsive platform or a dedicated mobile app is crucial. Mobile apps provide a more specialised and immersive user experience by utilising device-specific features like GPS, document scanning, and push notifications.

2. Second-Generation Enablers: Emerging Technologies

As organisations establish foundational technologies, they should look towards second-generation enablers. Although less mature, these technologies offer emerging digital opportunities, and can significantly enhance service differentiation. 

Emerging Technologies

Interactive Voice Response (IVR) systems improve the efficiency and effectiveness of digital services by routing callers to self-service options and providing relevant information without human intervention. These systems operate outside typical government agency working hours, ensuring continuous accessibility. Additionally, IVRs generate valuable data for future Voice of the Customer programs, improving overall service quality and responsiveness.

Digital Wallets facilitate transactions by expediting fund transfers and enhancing transparency through meticulous transaction records. They streamline administrative tasks, simplify transactions, and encourage service usage and adoption. 

AI-driven Virtual Agents or chatbots revolutionise customer interactions by providing 24/7 support. They offer prompt, efficient, and personalised services, enhancing customer satisfaction and trust. In resource-limited public sectors, virtual agents are cost-effective, optimising resource allocation and meeting growing service demands. Specialised virtual agents for specific sectors can further differentiate service providers.

3. Futuristic View: Ambitious Innovations

The futuristic view focuses on forward-looking technologies that address long-term roadblocks and offer transformative potential. These technologies are currently speculative but hold the promise of significantly reshaping the market.

Innovations

Subscription Management models enable public sector information services to be accessed in highly personalised ways, thereby enhancing citizen engagement. This model supports regulatory oversight by providing common data insights and improves the management of services, ultimately benefiting the public by ensuring more responsive and tailored information delivery.

AI concierge leverages advanced technologies like Natural Language Processing, Computer Vision, and Speech Technologies to provide personalised and proactive customer service. They redefine customer management, ensuring a seamless and tailored experience.

Immersive reality technologies, such as augmented and virtual reality (AR/VR) create captivating customer experiences by allowing interactions in virtual environments. These technologies establish a shared virtual environment, helping customers to engage with businesses and each other in new and immersive ways. As an emerging customer management tool, immersive reality can transform the dynamics of customer-business relationships, adding substantial value to the service experience.

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What Conversations Do We Need to Have About AI?

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In my earlier post this week, I referred to the need for a grown-up conversation on AI. Here, I will focus on what conversations we need to have and what the solutions to AI disruption might be. 

Three Levels of the AI Conversation

The Impact of AI on Individuals 

AI is likely to impact people a lot! You might lose your job to AI. Even if it is not that extreme, it’s likely AI will do a lot of your job. And it might not be the “boring bits” – and sometimes the boring bits make a job manageable! IT helpdesk professionals, for instance, are already reporting that AIOps means they only deal with the difficult challenges. While that might be fun to start with, some personality types find this draining, knowing that every problem that ends up in the queue might take hours or days to resolve. 

Your job will change. You will need new skills. Many organisations don’t invest in their employees, so you’ll need to upskill yourself in your own time and at your own cost. Look for employers who put new skill acquisition at the core of their employee offering. They are likelier to be more successful in the medium-to-long term and will also be the better employers with a happier workforce.  

The Impact of AI on Organisations 

Again – the impact on organisations will be huge. It will change the shape and size of organisations. We have already seen the impact in many industries.  The legal sector is a major example where AI can do much of the job of a paralegal. Even in the IT helpdesk example shared earlier, where organisations with a mature tech environment will employ higher skilled professionals in most roles. These sectors need to think where their next generation of senior employees will come from, if junior roles go to AI. Software developers and coders are seeing greater demand for their skills now, even as AI tools increasingly augment their work. However, these skills are at an inflection point, as solutions like TuringBots have already started performing developer roles and are likely to take over the job of many developers and even designers in the near future. 

Some industries will find that AI helps junior roles act more like senior employees, while others will use AI to perform the junior roles. AI will also create new roles (such as “prompt engineers”), but even those jobs will be done by AI in the future (and we are starting to see that).  

HR teams, senior leadership, and investors need to work together to understand what the future might look like for their organisations. They need to start planning today for that future. Hint: invest in skills development and acquisition – that’s what will help you to succeed in the future. 

The Impact of AI on the Economy 

Assuming the individual and organisational impacts play out as described, the economic impacts of widespread AI adoption will be significant, similar to the “Great Depression”. If organisations lay off 30% of their employees, that means 30% of the economy is impacted, potentially leading to drying up of some government and an increase in government spend on welfare etc. – basically leading to major societal disruption.  

The “AI won’t displace workers” narrative strikes me as the technological equivalent of climate change denial. Just like ignoring environmental warnings, dismissing the potential for AI to significantly impact the workforce is a recipe for disaster. Let’s not fall into the same trap and be an “AI denier”.  

What is the Solution?  

The solutions revolve around two ideas, and these need to be adopted at an industry level and driven by governments, unions, and businesses: 

  • Pay a living salary (for all citizens). Some countries already do this, with the Nordic nations leading the charge.  And it is no surprise that some of these countries have had the most consistent long-term economic growth. The challenge today is that many governments cannot afford this – and it will become even less affordable as unemployment grows. The solution? Changing tax structures, taxing organisational earnings in-country (to stop them recognising local earnings in low-tax locations), and taxing wealth (not incomes).  Also, paying essential workers who will not be replaced by AI (nurses, police, teachers etc.) better salaries will also help keep economies afloat. Easier said than done, of course! 
  • Move to a shorter work week (but pay full salaries). It is in the economic interest of every organisation that people stay gainfully employed. We have already discussed the ripple effect of job cuts. But if employees are given more flexibility, and working 3-day weeks, this not only spreads the work around more workers, but means that these workers have more time to spend money – ensuring continuing economic growth. Can every company do this? Probably not. But many can and they might have to. The concept of a 5-day work week isn’t that old (less than 100 years in fact – a 40-hour work week was only legislated in the US in the 1930s, and many companies had as little as 6-hour working days even in the 1950s). Just because we have worked this way for 80 years doesn’t mean that we will always have to. There is already a move towards 4-day work weeks. Tech.co surveyed over 1,000 US business leaders and found that 29% of companies with 4-day workweeks use AI extensively. In contrast, only 8% of organisations with a 5-day workweek use AI to the same degree. 

AI Changes Everything 

We are only at the beginning of the AI era. We have had a glimpse into the future, and it is both frightening and exciting. The opportunities for organisations to benefit from AI are already significant and will become even more as the technology improves and businesses learn to better adopt AI in areas where it can make an impact. But there will be consequences to this adoption. We already know what many of those consequences will be, so let’s start having those grown-up conversations today. 

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Making Concrete Change: Strategies for Carbon Reduction in Urban Development

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Despite an increase in energy efficiency investment, the construction sector’s energy consumption and CO₂ emissions have rebounded to an all-time high. Buildings currently contribute 39% of global energy-related carbon emissions – 28% from operational needs like heating and cooling, and 11% from construction materials.

In the next three decades, with the global population expected to reach 9.7 billion, the construction industry will face the pressure to meet growing infrastructure and housing demands while adapting to stricter environmental regulations.

The urgency of climate action demands that governments mandate low-carbon practices in urban development.

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Click here to download ‘Making Concrete Change: Strategies for Carbon Reduction in Urban Development’ as a PDF

Increase Use of Low-Carbon Materials

Traditional building materials like concrete, steel, and brick are strong and durable but environmentally costly. This high embodied carbon footprint is prompting a shift towards low-carbon alternatives. Indonesia is using ‘green cement’ – made using environmentally friendly materials – in the development of its new futuristic capital Nusantara. This has led to an estimated reduction in carbon emissions of up to 38% per tonne of cement so far.

Nordic countries are setting ambitious targets for low-carbon materials. Starting in 2025, Finland will require life cycle assessments and material declarations in construction to reduce emissions, detailing building components and material origins. Denmark is also prioritising low-carbon materials through energy-efficient designs, sustainable materials, and stringent building codes.

Mandate Whole-Life Carbon Emission Assessments

Whole Life-Cycle Carbon (WLC) emissions encompass all the carbon a building generates throughout its lifespan, from material extraction to demolition and disposal. Assessing WLC gives a comprehensive understanding of a building’s total environmental impact.

The London Plan is a roadmap for future development and achieving the goal of a zero-carbon city. The plan includes provisions for WLC analysis, specific energy hierarchies, and strategies to reduce London’s carbon footprint.

With a bold vision of a fully circular city by 2050, the Amsterdam Circular Strategy 2020-2025 lays out a comprehensive roadmap to achieve this goal. Key elements include mapping material flows to reduce reliance on virgin resources and mandating WLC assessments.

Enforce Clean Construction Standards

From green building codes to tax incentives, governments around the world are implementing innovative strategies to encourage sustainable building practices.

The Philippines’ National Building Code requires green building standards and energy efficiency measures for new buildings.

Seattle offers expedited permits for projects meeting embodied carbon standards, speeding up eco-friendly construction, and reinforcing the city’s environmental goals.

New Jersey offers businesses a tax credit of up to 5% for using low-carbon concrete and an additional 3% for concrete made with carbon capture technology.

Promote Large-Scale Adaptive Reuse

Large-scale adaptive reuse includes reducing carbon emissions by making existing buildings and infrastructure a larger part of the climate solution.

London’s Battersea Power Station restored its iconic chimneys and Art Deco façade, transforming it into a vibrant hub with residential, commercial, and leisure spaces.

The High Line in New York has been transformed into a public park with innovative landscaping, smart irrigation, and interactive art installations, enhancing visitor experience and sustainability.

Singapore using adaptive reuse to rejuvenate urban and industrial spaces sustainably. The Jurong Town Corporation is repurposing a terrace factory for sustainable redevelopment and preserving industrial heritage. In Queenstown, historical buildings in Tanglin Halt are being reused to maintain historical significance and add senior-friendly amenities.

Establish Circular Economy

As cities worldwide start exploring ways to go circular, some are already looking into different ways to leverage innovative practices to implement circular initiatives.

Toronto is embedding circular criteria into procurement by requiring circular economy profiles, vendor action plans, and encouraging circular design for parklets. The city also recommends actions for transitioning to a circular economy and is developing e-learning on circular procurement for staff.

Japan uses Building Information Modeling to optimise resource consumption and reduce waste during construction, with a focus on using recycled materials to promote sustainability in building projects.

Adopt Electric Vehicles

The share of EVs increased from 4% in 2020 to 18% in 2023 and is expected to grow in 2024. This trend reflects a global shift toward cleaner transportation, driven by technological advancements and rising environmental awareness.

The Delhi EV Policy aims to expand charging infrastructure and incentives, targeting 18,000 charging points by 2024, with 25% EV registrations and one charging outlet per 15 EVs citywide.

Singapore is adopting EVs to reduce land transport emissions as part of its net-zero goal, aiming to cut emissions by 1.5 to 2 million tonnes. The EV Roadmap targets cost parity with internal combustion engine (ICE) vehicles and 60,000 charging points by 2030.

Australia has set new rules to limit vehicle pollution, encouraging car makers to sell more electric vehicles and reduce transportation pollution.

Promote Circular Economy Marketplaces

Circular marketplaces play an important role in the new economy, changing the way we use, manufacture, and purpose materials and products.

The UK’s Material Reuse Portal aggregates surplus construction materials post-deconstruction, offering guidance and connections to service providers. It integrates with various data sources, can be customised for different locations, and provides free access to sustainable materials. Future plans include expanding marketplace partnerships to enhance material reuse.

Build Reuse is a US-based online marketplace specialising in salvaged and surplus building materials. It connects buyers and sellers for reclaimed items like wood, bricks, fixtures, and architectural elements, promoting resource efficiency and reducing construction waste.

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Time for a Grown-Up Conversation on AI: The Future Demands It

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If you have seen me present recently – or even spoken to me for more than a few minutes, you’ve probably heard me go on about how the AI discussions need to change!  At the moment, most senior executives, board rooms, governments, think tanks and tech evangelists are running around screaming with their hands on their ears when it comes to the impact of AI on jobs and society.

We are constantly being bombarded with the message that AI will help make knowledge workers more productive.  AI won’t take people’s jobs – in fact it will help to create new jobs – you get the drift; you’ve been part of these conversations!

I was at an event recently where a leading cloud provider had a huge slide with the words: “Humans + AI Together” in large font across the screen. They then went on to demonstrate an opportunity for AI. In a live demo, they had the customer of a retailer call a store to check for stock of a dress. The call was handled by an AI solution, which engaged in a natural conversation with the customer. It verified their identity, checked dress stock at the store, processed the order, and even confirmed the customer’s intent to use their stored credit card.

So, in effect, on one slide, the tech provider emphasised that AI was not going to take our jobs, and two minutes later they showed how current AI capabilities could replace humans – today!

At an analyst event last week, representatives from three different tech providers told analysts how Microsoft Copilot is freeing up 10-15 hours a week. For a 40-hour work week, that’s a 25-38 time saving. In France (where the work week is 35 hours), that’s up to 43% of their time saved. So, by using a single AI platform, we can save 25-43% of our time – giving us the ability to work on other things.

What are the Real Benefits of AI?

The critical question is: What will we do with this saved time? Will it improve revenue or profit for businesses? AI might make us more agile, faster, more innovative but unless that translates to benefits on the bottom line, it is pointless. For example, adopting AI might mean we can create three times as many products. However, if we don’t make any more revenue and/or profit by having three times as many products, then any productivity benefit is worthless. UNLESS it is delivered through decreased costs.

We won’t need as many humans in our contact centres if AI is taking calls. Ideally, AI will lead to more personalised customer experiences – which will drive less calls to the contact centre in the first place! Even sales-related calls may disappear as personal AI bots will find deals and automatically sign us up. Of course, AI also costs money, particularly in terms of computing power. Some of the productivity uplift will be offset by the extra cost of the AI tools and platforms.

Many benefits that AI delivers will become table stakes. For example, if your competitor is updating their product four times a year and you are updating it annually, you might lose market share – so the benefits of AI might be just “keeping up with the competition”. But there are many areas where additional activity won’t deliver benefits. Organisations are unlikely to benefit from three times more promotional SMSs or EDMs and design work or brand redesigns.

I also believe that AI will create new roles. But you know what? AI will eventually do those jobs too. When automation came to agriculture, workers moved to factories. When automation came to factories, workers moved to offices. The (literally) trillion-dollar question is where workers go when automation comes to the office.

The Wider Impact of AI

The issue is that very few senior people in businesses or governments are planning for a future where maybe 30% of jobs done by knowledge workers go to AI. This could lead to the failure of economies. Government income will fall off a cliff. It will be unemployment on levels not seen since the great depression – or worse. And if we have not acknowledged these possible outcomes, how can we plan for it?

This is what I call the “grown up conversation about AI”. This is acknowledging the opportunity for AI and its impacts on companies, industries, governments and societies. Once we acknowledge these likely outcomes we can plan for it.

And that’s what I’ll discuss shortly – look out for my next Ecosystm Insight: The Three Possible Solutions for AI-driven Mass Unemployment.

AI Research and Reports
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Beyond-Numbers-How-Data-Analysis-Paves-the-Way-for-AI-Careers
Beyond Numbers: How Data Analysis Paves the Way for AI Careers

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Data analysts play a vital role in today’s data-driven world, providing crucial insights that benefit decision-making processes. For those with a knack for numbers and a passion for uncovering patterns, a career as a data analyst can be both fulfilling and lucrative – it can also be a stepping stone towards other careers in data. While a data analyst focuses on data preparation and visualisation, an AI engineer specialises in creating AI solutions, a machine learning (ML) engineer concentrates on implementing ML models, and a data scientist combines elements of data analysis and ML to derive insights and predictions from data.

Tools, Skills, and Techniques of a Data Analyst

Excel Mastery. Unlocks a powerful toolbox for data manipulation and analysis. Essential skills include using a vast array of functions for calculations and data transformation. Pivot tables become your secret weapon for summarising and analysing large datasets, while charts and graphs bring your findings to life with visual clarity. Data validation ensures accuracy, and the Analysis ToolPak and Solver provide advanced functionalities for statistical analysis and complex problem-solving. Mastering Excel empowers you to transform raw data into actionable insights.

Advanced SQL. While basic skills handle simple queries, advanced users can go deeper with sorting, aggregation, and the art of JOINs to combine data from multiple tables. Common Table Expressions (CTEs) and subqueries become your allies for crafting complex queries, while aggregate functions summarise vast amounts of data.  Window functions add another layer of power, allowing calculations within query results.  Mastering Advanced SQL empowers you to extract hidden insights and manage data with unparalleled precision.

Data Visualisation. Crafts impactful data stories. These tools empower you to connect to various data sources, transform raw information into a usable format, and design interactive dashboards and reports. Filters and drilldowns allow users to explore your data from different angles, while calculated fields unlock deeper analysis. Parameters add a final touch of flexibility, letting viewers customise the report to their specific needs. With tools Tableau and Power BI, complex data becomes clear and engaging.

Essential Python. This powerful language excels at data analysis and automation. Libraries like NumPy and Pandas become your foundation for data manipulation and wrangling. Scikit-learn empowers you to build ML models, while SciPy and StatsModels provide a toolkit for in-depth statistical analysis.  Python’s ability to interact with APIs and web scrape data expands its reach, and its automation capabilities streamline repetitive tasks. With Essential Python, you have the power to solve complex problems.

Automating the Journey. Data analysts can be masters of efficiency, and their skills translate beautifully into AI. Scripting languages like Ansible and Terraform automate repetitive tasks. Imagine streamlining the process of training and deploying AI models – a skill that directly benefits the AI development pipeline. This proficiency in automation showcases the valuable foundation data analysts provide for building and maintaining AI systems.

Developing ML Expertise. Transitioning from data analysis to AI involves building on your existing skills to develop ML expertise. As a data analyst, you may start with basic predictive models. This knowledge is expanded in AI to include deep learning and advanced ML algorithms. Also, skills in statistical analysis and visualisation help in evaluating the performance of AI models.

Growing Your AI Skills  

Becoming an AI engineer requires building on a data analysis foundation to focus on advanced skills such as:

  • Deep Learning. Learning frameworks like TensorFlow and PyTorch to build and train neural networks.
  • Natural Language Processing (NLP). Techniques for processing and analysing large amounts of natural language data.
  • AI Ethics and Fairness. Understanding the ethical implications of AI and ensuring models are fair and unbiased.
  • Big Data Technologies. Using tools like Hadoop and Spark for handling large-scale data is essential for AI applications.

The Evolution of a Data Analyst: Career Opportunities

Data analysis is a springboard to AI engineering. Businesses crave talent that bridges the data-AI gap.  Your data analyst skills provide the foundation (understanding data sources and transformations) to excel in AI. As you master ML, you can progress to roles like:

  • AI Engineer. Works on integrating AI solutions into products and services. They work with AI frameworks like TensorFlow and PyTorch, ensuring that AI models are incorporated into products and services in a fair and unbiased manner.
  • ML Engineer. Focuses on designing and implementing ML models. They focus on preprocessing data, evaluating model performance, and collaborating with data scientists and engineers to bring models into production. They need strong programming skills and experience with big data tools and ML algorithms.
  • Data Scientist. Bridges the gap between data analysis and AI, often involved in both data preparation and model development. They perform exploratory data analysis, develop predictive models, and collaborate with cross-functional teams to solve complex business problems. Their role requires a comprehensive understanding of both data analysis and ML, as well as strong programming and data visualisation skills.

Conclusion

Hone your data expertise and unlock a future in AI! Mastering in-demand skills like Excel, SQL, Python, and data visualisation tools will equip you to excel as a data analyst. Your data wrangling skills will be invaluable as you explore ML and advanced algorithms. Also, your existing BI knowledge translates seamlessly into building and evaluating AI models. Remember, the data landscape is constantly evolving, so continue to learn to stay at the forefront of this dynamic field. By combining your data skills with a passion for AI, you’ll be well-positioned to tackle complex challenges and shape the future of AI.

The Future of AI
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Harnessing-Quantum-Potential-Government-and-Technology-Investments-for-Tomorrow
Harnessing Quantum Potential: Government and Technology Investments for Tomorrow

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Quantum computing is emerging as a groundbreaking force with the potential to reshape industries and enhance national security with unparalleled speed and precision. Governments and technology providers worldwide are heavily investing in this transformative technology, which promises significant advancements in areas such as cryptography, drug development, AI, and finance. Countries like Australia, Singapore, Taiwan, Qatar, and the UK are investing heavily in quantum research, backed by tech giants like Nvidia, IBM, and Google.

Ecosystm research finds that nearly 30% of enterprises are expecting to use quantum computing in the next 5 years.

Beyond Bits: Exploring the Potential of Quantum Computers

We need quantum computers because they have the potential to solve certain problems that are impossible (or impractical) for classical computers. Last year, Google led a study revealing that its quantum processor can complete a task in 6.18 seconds that would take a traditional supercomputer 47 years.

Here are a few reasons why quantum computing is exciting:

Unleashing the power of qubits. While classical computers use bits that can be either 0 or 1, quantum computers use qubits, which can exist in both states simultaneously (a state called superposition). This allows them to explore multiple possibilities simultaneously, making them significantly faster for specific tasks.

Tackling complex problems. Problems like simulating molecules or breaking complex encryption codes involve massive calculations. Quantum computers, with their unique properties, can manage these complexities more efficiently.

Revolutionising specific fields. Quantum computing has the potential to transform areas such as materials science, drug discovery, AI, and financial modelling. By simulating complex systems and processes, they could lead to breakthroughs in various sectors.

Quantum computers will not replace traditional computers entirely, but rather function as powerful tools for specific tasks beyond the reach of classical machines. Let’s look at cybersecurity as an example.

Twenty years ago, hacking was a basic task. Imagine a time before social media, when a simple computer and basic technical know-how were enough to breach a network. The stakes were low, the landscape uncomplicated. But technology, like threats, has evolved. Today’s hackers use sophisticated techniques, employing strategies like “harvest now, decrypt later” – stealing data today to decrypt later using more powerful machines. This is where quantum computing enters the scene, posing a significant threat to current encryption methods. In response, tech giants like Google, Apple, and Zoom are implementing quantum-resistant encryption into their software, safeguarding user data from potential future decryption attempts. Governments and telecommunication providers worldwide are boosting quantum encryption to tackle the potential security crisis.

The thrill of quantum computing lies in its infancy. Unforeseen applications, beyond our current imagination, could be unlocked as the technology matures.

Current Quantum Projects Focused on Security

First Scalable Network Secures Maritime Trade. The Netherlands is improving the resiliency of transport infrastructure in their own major international maritime hub, using quantum. The Port of Rotterdam Authority joined a collection of quantum technology firms to create a comprehensive cybersecurity ecosystem – the first of its kind globally. The port uses quantum technology to safeguard sensitive information, improving safety for the seagoing vessels carrying 470 million tonnes of cargo annually.

UK Integrates Quantum Navigation for Secure Air Travel. The UK is improving its digital transport infrastructure by integrating the first ever un-jammable aviation navigation system, powered by quantum software. This initiative was prompted by an incident where a government plane carrying the UK defence secretary had its GPS signal jammed close to Russian territory. This technology ensures safe and reliable navigation for aircraft, particularly in hostile environments. The UK government is investing USD 56 million into their quantum sector, aiming to become a quantum-enabled economy by 2033.

Governments Putting Faith in Quantum

Taiwan’s First Domestic 5-Qubit Computer. Taiwan is aiming to be a leader in quantum computing by building its first domestic machine by 2027. This initiative is part of a larger USD 259 million, five-year plan for quantum technology, and has a multi-pronged approach including building the actual quantum computer hardware; developing solutions to secure data in a world with quantum computers (quantum cryptography); creating a strong supply chain for quantum computing components within Taiwan; and collaborating with international partners to develop testing platforms and expertise.

Singapore Explores Real-World Applications. The Singaporean government has pledged USD 518 million to their National Quantum Strategy (NQS). This investment will provide the necessary resources to explore real-time applications of quantum technology in healthcare and technology. Simultaneously, they launched the National Quantum Processor Initiative (NQPI) to develop quantum sensors that will aid in research. Singapore aims to lead the world in quantum tech for investment portfolios, cryptography, and drug discovery.

Australia Aiming for World’s First Utility-Scale Machine. Backed by a USD 620 million investment from the Australian and Queensland governments, PsiQuantum aims to build a fault-tolerant computer that can solve previously challenging problems in fields like renewable energy, healthcare, and transportation. PsiQuantum’s innovative “fusion-based architecture” tackles scaling challenges by using millions of light-based qubits, paving the way for a new era of computational power and potentially sparking the next industrial revolution. This project positions Australia as a global leader in harnessing the immense potential of quantum computing.

Tech Companies Making the Quantum Leap

IBM Enhances Quantum Performance. IBM’s latest quantum computing platform, Qiskit 1.0, has worked on features that enhance performance, stability, and reliability. The updated open-source SDK aims to facilitate accessible quantum programming and accelerate processing times. Qiskit 1.0 uses optimised circuits to create and manage the interplay between classical and quantum computing. IBM is even collaborating with Japan’s AIST to develop a 10,000-qubit quantum computer by 2029, which is 75 times more powerful than current systems.

Microsoft and Quantinuum Achieve Reliable Logical Qubits. This significant milestone is said to mark a new era of dependable quantum technology, dramatically reducing errors and enhancing the precision of quantum computations. They have demonstrated an 800x improvement in error rates, paving the way for hybrid supercomputing systems that combine AI, high-performance computing (HPCs), and quantum capabilities to tackle scientific problems, with new capabilities becoming available to Azure Quantum Elements customers in the coming months.

Quantum Cloud Services for Enterprise. Major tech players QMware, Nvidia, and Oracle are teaming up to create hybrid quantum computing service for businesses. Combining classical and quantum computing, the project aims to crunch complex problems in AI, machine learning, and optimisation – all in the cloud.

Building Towards a Quantum Future

In the short term, using HPCs with quantum algorithms can already provide noticeable speed improvements over traditional methods. Hybrid approaches, where HPCs and quantum computers work together, could lead to significant gains in speed and efficiency, potentially ranging from 10x to 100x improvement.

Three strategies: quantum-inspired, hybrid, and full-scale quantum computing each offer distinct advantages.

While quantum-inspired computing leverages quantum algorithms to run on classical systems, hybrid computing combines classical and quantum processors, optimising the strengths of both to take complex problems more efficiently. Intuitively, full-scale quantum computing represents the ultimate goal, where large, fault-tolerant quantum computers solve problems beyond the reach of current classical systems.

Looking further ahead, the development of large-scale quantum computers could revolutionise industries by solving problems far beyond the reach of classical computers, with potential speedups of 500x to 1000x.

As quantum technology progresses, different industries and applications will benefit from tailored approaches that best suit their unique needs.

The Future of Industries
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