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Ecosystm Insights - Page 15 of 82 - A new age Technology Research platform to help you access latest market insights,expert opinions and research data
The-Shift-from-Predictive-AI-to-GenAI
The Shift from Predictive AI to GenAI: Implications on ROI

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The AI landscape is undergoing a significant transformation, moving from traditional predictive AI use cases towards Generative AI (GenAI). Currently, most GenAI use cases promise an improvement in employee productivity, without focusing on how to leverage this into new or additional revenue generating streams. This raises concerns about the long-term return on investment (ROI) if this is not adequately addressed. 

The Rise of Generative AI Over Predictive AI 

Traditionally, predictive AI has been integral to business strategies, leveraging data to forecast future outcomes with remarkable accuracy. Industries across the board have used predictive models for a range of applications, from demand forecasting in retail to fraud detection in finance. However, the tide is changing with the emergence of GenAI technologies. GenAI, capable of creating content, designing products, and even coding, holds the promise to revolutionise how businesses operate, innovate, and compete. 

The appeal of GenAI lies in its versatility and creativity, offering solutions that go beyond the capabilities of predictive models. For example, in the area of content creation, GenAI can produce written content, images, and videos at scale, potentially transforming marketing, entertainment, and education sectors. However, the current enthusiasm for GenAI’s productivity enhancements overshadows a critical aspect of technology adoption: monetisation. 

The Productivity Paradox 

While the emphasis on productivity improvements through GenAI applications is undoubtedly beneficial, there is a notable gap in exploring use cases that directly contribute to creating new revenue streams. This productivity paradox – prioritising operational efficiency and cost reduction – may not guarantee the sustained growth and ROI necessary from AI investments. 

True innovation in AI should not only aim at making existing processes more efficient but also at uncovering opportunities for monetisation. This involves leveraging GenAI to develop new products, services, or business models to access untapped markets or enhance customer value in ways that directly impact the bottom line. 

The Imperative for Strategic Reorientation 

Ignoring the monetisation aspect of GenAI applications poses a significant risk to the anticipated ROI from AI investments. As businesses allocate resources to AI adoption and integration, it’s also important to consider how these technologies can generate revenue, not just save costs. Without a clear path to monetisation, the investments in AI, particularly in the cutting-edge domain of GenAI, may not prove viable in the next financial year and beyond. 

To mitigate this risk, companies need to adopt a dual approach. First, they must continue to explore and exploit the productivity gains offered by GenAI, which are crucial for maintaining a competitive edge and achieving operational excellence. At the same time, businesses must strategically explore and invest in GenAI-driven opportunities for monetisation. This could mean innovating in product design, personalised customer experiences, or entirely new business models that were previously unfeasible. 

Conclusion 

The excitement around GenAI’s potential to transform industries is well-founded, but it must be tempered with strategic planning to ensure long-term viability and ROI. Businesses that recognise and act on the opportunity to not only improve productivity but also to monetise GenAI innovations will lead the next wave of growth in their respective sectors. The challenge lies in balancing the drive for efficiency with the pursuit of new revenue streams, ensuring that investments in AI deliver sustainable returns. As the AI landscape evolves, the ability to innovate in monetisation as much as in technology will distinguish the leaders from the followers. 

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Meeting Market Trends and Customer Demands​: Analyst Guidance for Tech Providers

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2024 has started cautiously for organisations, with many choosing to continue with tech projects that have already initiated, while waiting for clearer market conditions before starting newer transformation projects. This means that tech providers must continue to refine their market messaging and enhance their service/product offerings to strengthen their market presence in the latter part of the year. Ecosystm analysts present five key considerations for tech providers as they navigate evolving market and customer trends, this year.

Navigating Market Dynamics

As organisations refine their AI approaches, tech providers must adjust their market strategies - Sash Mukherjee

Continuing Economic Uncertainties​. Organisations will focus on ongoing projects and consider expanding initiatives in the latter part of the year.​ This means that tech providers should maintain visibility and trust with existing clients. They also need to help their customers meet multiple KPIs. 

Popularity of Generative AI​. For organisations, this will be the time to go beyond the novelty factor and assess practical business outcomes, allied costs, and change management.​ Tech providers need to include ROI discussions for short-term and mid-term perspectives as organisations move beyond pilots.​

Infrastructure Market Disruption​. Tech leaders will keep an eye out for advancements and disruptions in the market (likely to originate from the semiconductor sector)​. The disruptions might require tech vendors to re-assess the infrastructure partner ecosystem.

Need for New Tech Skills. Tech leaders will evaluate Generative AI’s impact on AIOps and IT Architecture; invest in upskilling for talent retention.​ Tech providers must prioritise creating user-friendly experiences to make technology accessible to business users. Training and partner enablement will also need a higher focus.

​Increased Focus on Governance​. Tech leaders will consult tech vendors on how to implement safeguards for data usage, sharing, and cybersecurity.​ This opens up opportunities in offering governance-related services.​

5 Key Considerations for Tech Vendors

Click here to download ‘Meeting Market Trends and Customer Demands​: Analyst Guidance for Tech Providers’ as a PDF.

#1 Get Ready for the Year of the AI Startup

Get Ready for the Year of the AI Startup - Tim Sheedy

While many AI companies have been around for years, this will be the year that many of them make a significant play into enterprises in Asia Pacific. This comes at a time when many organisations are attempting to reduce tech debt and simplify their tech architecture. ​

For these AI startups to succeed, they will need to create watertight business cases, and do a lot of the hard work in pre-integrating their solutions with the larger platforms to reduce the time to value and simplify the systems integration work.​

To respond to these emerging threats, existing tech providers will need to not only accelerate their own use of AI in their platforms, but also ramp up the education and promotion of these capabilities. 

#2 Lead With Data, Not AI Capabilities 

Lead With Data, Not AI Capabilities - Darian Bird

Organisations recognise the need for AI to enhance their workforce, improve customer experience, and automate processes. However, the initial challenge lies in improving data quality, as trust in early AI models hinges on high-quality training data for long-term success.​

Tech vendors that can help with data source discovery, metadata analysis, and seamless data pipeline creation will emerge as trusted AI partners. Transformation tools that automate deduplication and quality assurance tasks empower data scientists to focus on high-value work. Automation models like Segment Anything enhance unstructured data labeling, particularly for images. Finally synthetic data will gain importance as quality sources become scarce.​

Tech vendors will be tempted to capitalise on the Generative AI hype but for sake of positive early experiences, they should begin with data quality.​

​​#3 Prepare Thoroughly for AI-driven Business Demand 

Prepare Thoroughly for AI-driven Business Demand - Achim Granzen

Besides pureplay AI opportunities, AI will drive a renewed and increased interest in data and data management. Tech and service providers can capitalise on this by understanding the larger picture around their clients’ data maturity and governance. Initial conversations around AI can be door openers to bigger, transformational engagements.​

Tech vendors should avoid the pitfall of downplaying AI risks. Instead, they should make all efforts to own and drive the conversation with their clients. They need to be forthcoming about their in-house responsible AI guidelines and understand what is happening in AI legislation world-wide (hint: a lot!) ​

Tech providers must establish strong client partnerships for AI initiatives to succeed. They must address risk and benefit equally to reap the benefits of larger AI-driven transformation engagements. ​

#4 Converge Network & Security Capabilities 

Converge Network & Security Capabilities- Darian Bird

Networking and security vendors will need to develop converged offerings as these two technologies increasingly overlap in the hybrid working era. Organisations are now entering a new phase of maturity as they evolve their remote working policies and invest in tools to regain control. They will require simplified management, increased visibility, and to provide a consistent user experience, wherever employees are located.​

There has already been a widespread adoption of SD-WAN and now organisations are starting to explore next generation SSE technologies. Procuring these capabilities from a single provider will help to remove complexity from networks as the number of endpoints continue to grow. ​

Tech providers should take a land and expand approach, getting a foothold with SASE modules that offer rapid ROI. They should focus on SWG and ZTNA deals with an eye to expanding in CASB and FWaaSas customers gain experience.

#5 Double Down on Your Partner Ecosystem

Double Down on Your Partner Ecosystem - Tim Sheedy

The IT services market, particularly in Asia Pacific, is poised for significant growth. Factors, including the imperative to cut IT operational costs, the growing complexity of cloud migrations and transformations, change management for Generative AI capabilities, and rising security and data governance needs, will drive increased spending on IT services.​

Tech services providers – consultants, SIs, managed services providers, and VARs – will help drive organisations’ tech spend and strategy. This is a good time to review partners, evaluating whether they can take the business forward, or whether there is a need to expand or change the partner mix.​

Partner reviews should start with an evaluation of processes and incentives to ensure they foster desired behaviour from customers and partners. Tech vendors should develop a 21st century partner program to improve chances of success.  ​

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Ecosystm VendorSphere: Red Hat’s Strategic Positioning

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At the end of last year, I had the privilege of attending a session organised by Red Hat where they shared their Asia Pacific roadmap with the tech analyst community. The company’s approach of providing a hybrid cloud application platform centred around OpenShift has worked well with clients who favour a hybrid cloud approach. Going forward, Red Hat is looking to build and expand their business around three product innovation focus areas. At the core is their platform engineering, flanked by focus areas on AI/ML and the Edge.

The Opportunities

Besides the product innovation focus, Red Hat is also looking into several emerging areas, where they’ve seen initial client success in 2023. While use cases such as operational resilience or edge lifecycle management are long-existing trends, carbon-aware workload scheduling may just have appeared over the horizon. But two others stood out for me with a potentially huge demand in 2024. 

GPU-as-a-Service. GPUaaS addresses a massive demand driven by the meteoric rise of Generative AI over the past 12 months. Any innovation that would allow customers a more flexible use of scarce and expensive resources such as GPUs can create an immediate opportunity and Red Hat might have a first mover and established base advantage. Particularly GPUaaS is an opportunity in fast growing markets, where cost and availability are strong inhibitors. 

Digital Sovereignty. Digital sovereignty has been a strong driver in some markets – for example in Indonesia, which has led to most cloud hyperscalers opening their data centres onshore over the past years. Yet not the least due to the geography of Indonesia, hybrid cloud remains an important consideration, where digital sovereignty needs to be managed across a diverse infrastructure. Other fast-growing markets have similar challenges and a strong drive for digital sovereignty. Crucially, Red Hat may well have an advantage where onshore hyperscalers are not yet available (for example in Malaysia). 

Strategic Focus Areas for Red Hat

Red Hat’s product innovation strategy is robust at its core, particularly in platform engineering, but needs more clarity at the periphery. They have already been addressing Edge use cases as an extension of their core platform, especially in the Automotive sector, establishing a solid foundation in this area. Their focus on AI/ML may be a bit more aspirational, as they are looking to not only AI-enable their core platform but also expand it into a platform to run AI workloads. AI may drive interest in hybrid cloud, but it will be in very specific use cases.  

For Red Hat to be successful in the AI space, it must steer away from competing straight out with the cloud-native AI platforms. They must identify the use cases where AI on hybrid cloud has a true advantage. Such use cases will mainly exist in industries with a strong Edge component, potentially also with a still heavy reliance on on-site data centres. Manufacturing is the prime example.  

Red Hat’s success in AI/ML use cases is tightly connected to their (continuing) success in Edge use cases, all build on the solid platform engineering foundation. 

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Anticipating Tech Advances and Disruptions​: Strategic Guidance for Technology Leaders

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2024 will be another crucial year for tech leaders – through the continuing economic uncertainties, they will have to embrace transformative technologies and keep an eye on market disruptors such as infrastructure providers and AI startups. Ecosystm analysts outline the key considerations for leaders shaping their organisations’ tech landscape in 2024.​

Navigating Market Dynamics

Market Trends that will impact organisations' tech investments and roadmap in 2024 - Sash Mukherjee

Continuing Economic Uncertainties​. Organisations will focus on ongoing projects and consider expanding initiatives in the latter part of the year.​

Popularity of Generative AI​. This will be the time to go beyond the novelty factor and assess practical business outcomes, allied costs, and change management.​

Infrastructure Market Disruption​. Keeping an eye out for advancements and disruptions in the market (likely to originate from the semiconductor sector)​ will define vendor conversations.

Need for New Tech Skills​. Generative AI will influence multiple tech roles, including AIOps and IT Architecture. Retaining talent will depend on upskilling and reskilling. ​

Increased Focus on Governance​. Tech vendors are guide tech leaders on how to implement safeguards for data usage, sharing, and cybersecurity.​

5 Key Considerations for Tech Leaders​

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Click here to download ‘Anticipating ​ Tech Advances and Disruptions​: Strategic Guidance for Technology Leaders’ as a PDF.

#1 Accelerate and Adapt: Streamline IT with a DevOps Culture 

Over the next 12-18 months, advancements in AI, machine learning, automation, and cloud-native technologies will be vital in leveraging scalability and efficiency. Modernisation is imperative to boost responsiveness, efficiency, and competitiveness in today’s dynamic business landscape.​

The continued pace of disruption demands that organisations modernise their applications portfolios with agility and purpose. Legacy systems constrained by technical debt drag down velocity, impairing the ability to deliver new innovative offerings and experiences customers have grown to expect. ​

Prioritising modernisation initiatives that align with key value drivers is critical. Technology leaders should empower development teams to move beyond outdated constraints and swiftly deploy enhanced applications, microservices, and platforms. ​

Accelerate and Adapt: Streamline IT with a DevOps Culture - Clay Miller

#2 Empowering Tomorrow: Spring Clean Your Tech Legacy for New Leaders

Modernising legacy systems is a strategic and inter-generational shift that goes beyond simple technical upgrades. It requires transformation through the process of decomposing and replatforming systems – developed by previous generations – into contemporary services and signifies a fundamental realignment of your business with the evolving digital landscape of the 21st century.​

The essence of this modernisation effort is multifaceted. It not only facilitates the integration of advanced technologies but also significantly enhances business agility and drives innovation. It is an approach that prepares your organisation for impending skill gaps, particularly as the older workforce begins to retire over the next decade. Additionally, it provides a valuable opportunity to thoroughly document, reevaluate, and improve business processes. This ensures that operations are not only efficient but also aligned with current market demands, contemporary regulatory standards, and the changing expectations of customers.​

Empowering Tomorrow: Spring Clean Your Tech Legacy for New Leaders - Peter Carr

#3 Employee Retention: Consider the Strategic Role of Skills Acquisition

The agile, resilient organisation needs to be able to respond at pace to any threat or opportunity it faces. Some of this ability to respond will be related to technology platforms and architectures, but it will be the skills of employees that will dictate the pace of reform. While employee attrition rates will continue to decline in 2024 – but it will be driven by skills acquisition, not location of work.  ​

Organisations who offer ongoing staff training – recognising that their business needs new skills to become a 21st century organisation – are the ones who will see increasing rates of employee retention and happier employees. They will also be the ones who offer better customer experiences, driven by motivated employees who are committed to their personal success, knowing that the organisation values their performance and achievements. ​

Employee Retention: Consider the Strategic Role of Skills Acquisition - Tim Sheedy

#4 Next-Gen IT Operations: Explore Gen AI for Incident Avoidance and Predictive Analysis

The integration of Generative AI in IT Operations signifies a transformative shift from the automation of basic tasks, to advanced functions like incident avoidance and predictive analysis. Initially automating routine tasks, Generative AI has evolved to proactively avoiding incidents by analysing historical data and current metrics. This shift from proactive to reactive management will be crucial for maintaining uninterrupted business operations and enhancing application reliability. ​

Predictive analysis provides insight into system performance and user interaction patterns, empowering IT teams to optimise applications pre-emptively, enhancing efficiency and user experience. This also helps organisations meet sustainability goals through accurate capacity planning and resource allocation, also ensuring effective scaling of business applications to meet demands. ​

Next-Gen IT Operations: Explore Gen AI for Incident Avoidance and Predictive Analysis - Richard Wilkins

#5 Expanding Possibilities: Incorporate AI Startups into Your Portfolio

While many of the AI startups have been around for over five years, this will be the year they come into your consciousness and emerge as legitimate solutions providers to your organisation. And it comes at a difficult time for you! ​

Most tech leaders are looking to reduce technical debt – looking to consolidate their suppliers and simplify their tech architecture. Considering AI startups will mean a shift back to more rather than fewer tech suppliers; a different sourcing strategy; more focus on integration and ongoing management of the solutions; and a more complex tech architecture. ​

To meet business requirements will mean that business cases will need to be watertight – often the value will need to be delivered before a contract has been signed. ​

Expanding Possibilities: Incorporate AI Startups into Your Portfolio - Tim Sheedy
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Evolving Landscape: AI Startups Take Centre Stage in 2024

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The tech industry tends to move in waves, driven by the significant, disruptive changes in technology, such as cloud and smartphones. Sometimes, it is driven by external events that bring tech buyers into sync – such as Y2K and the more recent pandemic. Some tech providers, such as SAP and Microsoft, are big enough to create their own industry waves. The two primary factors shaping the current tech landscape are AI and the consequential layoffs triggered by AI advancements. 

While many of the AI startups have been around for over five years, this will be the year they emerge as legitimate solutions providers to organisations. Amidst the acceleration of AI-driven layoffs, individuals from these startups will go on to start new companies, creating the next round of startups that will add value to businesses in the future. 

Tech Sourcing Strategies Need to Change 

The increase in startups implies a change in the way businesses manage and source their tech solutions. Many organisations are trying to reduce tech debt, by typically consolidating the number of providers and tech platforms. However, leveraging the numerous AI capabilities may mean looking beyond current providers towards some of the many AI startups that are emerging in the region and globally. 

The ripple effect of these decisions is significant. If organisations opt to enhance the complexity of their technology architecture and increase the number of vendors under management, the business case must be watertight. There will be less of the trial-and-error approach towards AI from 2023, with a heightened emphasis on clear and measurable value. 

AI Startups Worth Monitoring 

Here is a selection of AI startups that are already starting to make waves across Asia Pacific and the globe. 

  • ADVANCE.AI provides digital transformation, fraud prevention, and process automation solutions for enterprise clients. The company offers services in security and compliance, digital identity verification, and biometric solutions. They partner with over 1,000 enterprise clients across Southeast Asia and India across sectors, such as Banking, Fintech, Retail, and eCommerce. 
  • Megvii is a technology company based in China that specialises in AI, particularly deep learning. The company offers full-stack solutions integrating algorithms, software, hardware, and AI-empowered IoT devices. Products include facial recognition software, image recognition, and deep learning technology for applications such as consumer IoT, city IoT, and supply chain IoT. 
  • I’mCloud is based in South Korea and specialises in AI, big data, and cloud storage solutions. The company has become a significant player in the AI and big data industry in South Korea. They offer high-quality AI-powered chatbots, including for call centres and interactive educational services. 
  • H2O.ai provides an AI platform, the H2O AI Cloud, to help businesses, government entities, non-profits, and academic institutions create, deploy, monitor, and share data models or AI applications for various use cases. The platform offers automated machine learning capabilities powered by H2O-3, H2O Hydrogen Torch, and Driverless AI, and is designed to help organisations work more efficiently on their AI projects. 
  • Frame AI provides an AI-powered customer intelligence platform. The software analyses human interactions and uses AI to understand the driving factors of business outcomes within customer service. It aims to assist executives in making real-time decisions about the customer experience by combining data about customer interactions across various platforms, such as helpdesks, contact centres, and CRM transcripts. 
  • Uizard offers a rapid, AI-powered UI design tool for designing wireframes, mockups, and prototypes in minutes. The company’s mission is to democratise design and empower non-designers to build digital, interactive products. Uizard’s AI features allow users to generate UI designs from text prompts, convert hand-drawn sketches into wireframes, and transform screenshots into editable designs. 
  • Moveworks provides an AI platform that is designed to automate employee support. The platform helps employees to automate tasks, find information, query data, receive notifications, and create content across multiple business applications. 
  • Tome develops a storytelling tool designed to reduce the time required for creating slides. The company’s online platform creates or emphasises points with narration or adds interactive embeds with live data or content from anywhere on the web, 3D renderings, and prototypes. 
  • Jasper is an AI writing tool designed to assist in generating marketing copy, such as blog posts, product descriptions, company bios, ad copy, and social media captions. It offers features such as text and image AI generation, integration with Grammarly and other Chrome extensions, revision history, auto-save, document sharing, multi-user login, and a plagiarism checker. 
  • Eightfold AI provides an AI-powered Talent Intelligence Platform to help organisations recruit, retain, and grow a diverse global workforce. The platform uses AI to match the right people to the right projects, based on their skills, potential, and learning ability, enabling organisations to make informed talent decisions. They also offer solutions for diversity, equity, and inclusion (DEI), skills intelligence, and governance, among others. 
  • Arthur provides a centralised platform for model monitoring. The company’s platform is model and platform agnostic, and monitors machine learning models to ensure they deliver accurate, transparent, and fair results. They also offer services for explainability and bias mitigation. 
  • DNSFilter is a cloud-based, AI-driven content filtering and threat protection service, that can be deployed and configured within minutes, requiring no software installation. 
  • Spot AI specialises in building a modern AI Camera System to create safer workplaces and smarter operations for every organisation. The company’s AI Camera System combines cloud and edge computing to make video footage actionable, allowing customers to instantly surface and resolve problems. They offer intelligent video recorders, IP cameras, cloud dashboards, and advanced AI alerts to proactively deliver insights without the need to manually review video footage. 
  • People.ai is an AI-powered revenue intelligence platform that helps customers win more revenue by providing sales, RevOps, marketing, enablement, and customer success teams with valuable insights. The company’s platform is designed to speed up complex enterprise sales cycles by engaging the right people in the right accounts, ultimately helping teams to sell more and faster with the same headcount.  

These examples highlight a few startups worth considering, but the landscape is rich with innovative options for organisations to explore. Similar to other emerging tech sectors, the AI startup market will undergo consolidation over time, and incumbent providers will continue to improve and innovate their own AI capabilities. Till then, these startups will continue to influence enterprise technology adoption and challenge established providers in the market.

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