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How Should CFOs Think About Approving AI Spending?

By Brian Unruh is Chief Financial Officer (CFO) at ABBYY

When you hear your dentist talk about the use of artificial intelligence, you know it’s permeated every aspect of our day-to-day life. Yet, you’ve probably already had more intense c-suite discussions about the product roadmap, resources, and the ever-important topic – budget. It’s imperative for the CFO office to understand how AI can impact budgets – and not just in spending.

Relating to spending, a recent global survey by ABBYY reported that 82% of enterprise leaders increased their AI budgets in 2023. Most attributed a 2x return on investment and notable impact to accelerating product quality, delivering value to customers, and improving workers’ productivity. IDC affirms this trend and forecasts AI software revenue will grow to $251 billion by 2027. It sounds like a no-brainer to jump on the AI bandwagon, but not all AI is created equal. To contribute meaningful discussion to AI budget considerations, here are a few important factors CFOs should know before they approve AI spending.

Insist on purpose-built AI

Generic AI tools like ChatGPT can be alluring. There is so much anticipation for them in the market that IDC estimates generative AI spending will reach $143 billion in 2027. However, tools like ChatGPT are constructed of large language models (LLMs) built on one trillion-plus parameters (equivalent to over 1 million books) and optimised for everything but what would help the finance office the most – a document.

Brian Unruh

As a result, generic AI tools can provide slower performance in processing the output you want, waste energy, and significantly waste power consumption to the equivalent of powering a small island. Suppose all these side effects weren’t already unacceptable within organisations trying to minimise costs and risks. In that case, it can deliver inconsistent results and even hallucinations, making it difficult for humans in the loop to know when an answer is correct and how to address the error so it does not repeat.

Alternatively, purpose-built AI narrows the context and task to the core of what it needs, so it achieves the results the business needs. That also has been tested against a focused data set of the world’s most complex documents rampant throughout enterprises. These include invoices, POs, customer correspondences, claims forms, tax forms, and hundreds of other documents that drive a business.

When talking with your innovation leaders and technology partners, ensure the AI they recommend is purpose-built for the specific business problem and has proven results that deliver on a consistent basis.

Approve AI for revenue-generating processes

Economic concerns with inflation and high-interest rates compounded by a reduced labor force do not leave room for technological trial and error. Unless your organisation is developing and testing AI models, your IT budget should incorporate tech investments leveraging AI to improve the customer experience, operational excellence, and revenue.

Prudent CFOs have the fiduciary responsibility to advocate for AI tools to augment workers’ productivity and accelerate the straight-through processing of any business process impacting revenue. Ernst & Young states their clients leverage AI to streamline their operations at the front or back end.

For example, the heart of every organisation is accounts payables. Using purpose-built AI to streamline the processing and timing of invoice payments and purchase orders will greatly improve cash cycle outcomes. In this scenario, AI-powered document processing will read, understand, and classify critical financial data into ERP systems.

In other industries, such as healthcare, AI can expedite the review of medical records to approve patient referrals to see specialists and receive life-saving medications. For manufacturers and fast-moving consumer goods (FMCG) producers, customs clearance can be expedited across borders to get products to store shelves and consumers’ tables faster.

Understand the actual cost of AI

Whenever a new tech trend emerges, you risk vendors overpromising capabilities. Ensure the details are noted in service level agreements about performance, compute utilisation and precision of outcomes. Also, consider the cost for self-training generative AI models varies from as low as MosaicML’s model at $325K to $6.75M for Google’s PaLM model and as much as $100K a day for OpenAI’s ChatGPT. While the usage costs for ChatGPT Plus are available by a subscription-based model, consider the business use case and the number of users needed to complete enterprise-level document processing.

As mentioned, purpose-built AI can put enterprises’ information to work at scale at significantly lower costs and higher-level valued outcomes and consistencies.

The democratisation of AI means solutions should be available in low-code/no-code applications that can plug into your enterprise systems with pre-built model training available out-of-the-box. For example, AI used in document processing can identify, understand, and classify data within invoices with up to 95% accuracy and automatically process them 81% faster than humans. Furthermore, it has been proven to increase employee productivity by up to 400% and lower processing costs by 91%. These cost savings can be directly tied to project ROI and profitability.

Overall, CFOs can be more confident in approving AI budgets by getting answers to the following questions:

  1. Does the AI solution address the business problem or opportunity?
  2. Can the AI vendor provide evidence of success?
  3. Is the AI solution rooted in ethical and responsible practices?
  4. Does the vendor offer ongoing support and improvement post-adoption?

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Business

Need for speed: The importance of businesses acting fast!

John Kelleher, VP UKI & ME, UiPath

With significant economic disruption over the past few years, the ability to adapt to changing circumstances quickly has never been more important for businesses. Increasingly, there are instances of sudden pressure on organisations to adopt the latest technology, such as the push to move to cloud computing models or embrace artificial intelligence (AI).

In the past couple of years, the AI industry has thrived as the technology becomes indispensable for businesses. From chatbots to aid customer service interactions, to machine learning models that produce accurate financial forecasts, AI has found a place in all areas of business.

Soon, AI will become the standard customers expect, meaning organisations must adopt it at pace. Those who manage to implement the technology correctly will reap benefits in productivity, employee satisfaction and, ultimately, profitability. But to do this, organisations need to transform how they operate.

Customers won’t be patient

In an AI-driven world, patience is a virtue of the past. The expectations of service delivery and response times have drastically changed as the norm becomes swift response times delivered from digital-first organisations.

Customers continue to prioritise convenience with the purchases they make and demand more from the organisations they are loyal to. This ‘convenience economy’ is also lucrative for businesses as customers are willing to pay a 5% premium for convenience, which rises among younger consumers.

With these customer demands, the convenience attached to a business is a point of differentiation in a competitive marketplace. However, it is not possible to provide a service at pace unless the business offering it is set up in the right way.

The important takeaway from this is speed should be the top priority for businesses. With companies across all industries increasingly adopting AI to transform the services they offer, and the experiences customers have, convenience is no longer a competitive differentiator – it is a necessity. Businesses need to get ahead of the curve to ensure they don’t lose out to competitors.

Speed as a core business value

The capacity for your business to respond quickly to emerging market conditions and offer innovation at pace doesn’t only influence the experience for customers, but is transformative to how a business operates. Promoting speed and flexibility in internal business operations can support organisations to adapt quickly to any external challenges and uncertainties faster than their competitors.

Supply chains have experienced significant unforeseen disruption in recent years, and this has caused shortages, delays, and increased costs. For companies to stay ahead in this increasingly volatile environment, they must be prepared for uncertainty and be able to adapt to deliver at a fast pace for consumers. Across uses such as inventory management, supplier analysis and demand forecasting, AI can be an effective tool in boosting speed, in both issue identification and handling possible fall out should something go wrong. We’re already starting to see new expectations being set for supply chain organisations in response to this, with 50% expected to invest in AI and advanced analytics to prepare themselves for unexpected delays and disruption.

Another area speed is invaluable to is complying with increasingly complex regulation. Around 34% of businesses globally are using AI for regulatory compliance already, and businesses need to maximise this opportunity. The ripple effects of falling behind on compliance can’t be overstated. From adjusting privacy protocols and HR policies to incorporating updated environmental guidelines, move too slowly and you could see heavy fines, legal repercussions or a tarnished reputation.

AI and automation are key to accelerate business functions

AI and automation are key to helping organisations streamline processes and innovate faster. By simplifying how a business operates and reducing time spent on repetitive work, 90% of employees report a significant boost to productivity. Further, AI and automation can help predict and manage employee’s workloads better. If provided with the right data, AI algorithms have the capacity to predict and offer recommendations on business decisions, helping to eliminate crunch periods.

Integrating AI into your business’s workflows provides flexibility, productivity, and the capacity to handle unanticipated events. Companies will be able to respond faster to changes and manage their operations better and, as AI and automation are used to remove the repetitive drudgery from people’s work, employee satisfaction will improve.

Harnessing efficiency to maximise opportunity

Investing in AI and implementing it quickly is now a business imperative. Businesses in the UK are increasingly open to using AI as the number of UK AI companies has grown by over 600% over the last 10 years.  Rapid implementation of AI not only enhances efficiency but also ensures companies can capitalise on new opportunities before other competitors do. Those who take advantage of AI will be better prepared to anticipate trends, refine the customer experience and improve their bottom line.

Operational efficiency creates a more favourable cost structure and boosts margins. Ensuring compliance mitigates risks and helps companies avoid fines and reputational harm while streamlining customer service not only lowers costs and reduces turnover but also strengthens customer retention and acquisition, driving top-line growth.

Today, more than ever, time is money.

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Business

Wearable AI: How to supercharge adoption of consumer wearable devices 

By Kevin Brundish, CEO of LionVolt 

As we look toward the future, the global wearables market is projected to reach $265.4 billion by 2026. This growth is further fuelled by advancements in AI, which promise to enhance the functionality and performance of wearable devices. For instance, in the healthcare industry, artificial intelligence (AI) may use the massive volumes of data gathered by wearables to communicate with patients and offer precise diagnosis, advice and support.

Despite the remarkable features and capabilities of modern wearable devices, battery life remains a significant challenge. Most smartwatches, for example, still struggle to last a full 24 hours, making it difficult for users to monitor sleep patterns and daily activities continuously without frequent recharging. With the use of AI and applications that demand increasing amounts of data, this limitation prevents wearables from becoming fully integrated tools in our daily lives.

Advances in battery technology are looking to address this issue. At LionVolt we are working on a 3D lithium-metal anode technology which helps to significantly enhance lithium-ion battery performance.

Smaller Batteries, Same Energy 

The most significant advantage of lithium-metal anode batteries is their ability to provide the same energy from a smaller size battery. This gives designers greater freedom and opens new possibilities for wearable technology by enabling the miniaturisation of existing wearable designs. In addition, lithium-metal anodes may allow manufacturers to lower overall prices by moving away from costly cathode materials they use now, to cathode materials being used in automotive industry, where there is a cost advantage through economies of scale. 

Higher Energy Density and Faster Charging Times 

When we compare conventional lithium-ion batteries to lithium-metal anode battery technology, the lithium-metal anode batteries have a superior energy density. For users of wearable devices, this translates to longer usage periods and fewer charging interruptions as well as faster charge times, which minimises downtime and guarantees that gadgets remain operational when needed.

Enhanced User Experience 

Fast charging periods and increased energy density which is key to longer usage periods improve wearable technology’s overall performance, enabling consumers to maximise its benefits without sacrificing dependability or quality

Lithium-metal anode powered batteries also improve wearable gadgets’ dependability and durability. Users can count on their wearables to function reliably day or night and to enable a variety of applications, such as health monitoring and exercise tracking. These batteries are made to endure the demands of regular use, guaranteeing that gadgets continue to be reliable and operational for long stretches of time. 

The use of the highest performing materials in wearables typically comes at a high cost. However, with the advancement of new technology, it becomes possible to utilize more widely available and cost-effective anodes without compromising on performance. This approach allows for the efficient operation of wearables while also offering a cost benefit, addressing the economic challenges associated with high-performance materials.

Overcoming Adoption Barriers 

One of the key reasons for the slower adoption rate of consumer wearables is the charging rate. The utility of these products can be increased, along with their consumer appeal by extending their battery life and charging timeframes. The advantages of the next generation of batteries—faster charging, longer battery life, and improved device dependability—can greatly accelerate wearables’ uptake.  

Advancing Wearable Technology 

By tackling the crucial problem of battery duration, coupled with a fast charge capability, lithium-metal anode technology would propel the wearables business forward. An emphasis on sustainability and safety guarantees that these developments help both consumers and the environment, while our smaller, more efficient batteries provide designers the freedom to develop creative new gadgets. 

Transforming the Landscape of Wearable Technology

Lithium-metal anode battery technology brings numerous benefits to the consumer wearables sector: 

  • Longer Battery Life: Wearable devices will last much longer on a single charge, addressing a significant pain point for users. 
  • Increased Monitoring Time: Faster charging means users can monitor their health and activities for extended periods without interruption. 
  • Reduced Equipment Needs: With longer battery life and faster charging, users will need fewer duplicate products to cover charging times, simplifying their tech ecosystem.

Imagine being able to monitor your heart activity and more to manage health conditions without worrying if your device has enough power? With improved battery longevity, users can rely on their wearables for consistent health insights, making it easier to identify trends and make informed lifestyle changes. This seamless integration into daily life not only promotes better health management but also empowers users to take proactive steps towards their well-being.

These enhancements not only improve the user experience but also pose the potential to increase the adoption rate of consumer wearables.

Looking Ahead: Shaping the Future of Wearable Technology 

Wearables have a bright future because of AI and cutting-edge battery technology, which will greatly enhance their usability, dependability and functionality. The next generation of batteries are revolutionising the wearables market and paving the way for a new era of technological innovation by emphasising sustainability, increased energy density, quicker charging times, and improved safety features. 

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Business

The Future of Observability: Empowering businesses through data-driven transformation

 Karthik SJ, General Manager AI, LogicMonitor

The tech industry is at the cusp of a revolution, where digital transformation has shifted from aspiration to necessity. At its heart lies observability – a critical enabler for organisations navigating the complexity of modern IT infrastructures. Observability goes beyond monitoring systems or tracking performance; it transforms vast streams of system data into actionable insights that drive real-time decisions, improve operational efficiency, and ensure business resilience. 

Observability: The foundation of digital transformation

The digital transformation journey requires businesses to adopt a more sophisticated approach to managing their IT ecosystems. As organisations scale and evolve, they rely on a growing array of technologies, from cloud services to hybrid infrastructures, microservices, and containers. Parallel to increasing complexity, is a need for more granular visibility into system performance, security, and user experience.

This is where observability becomes essential, unlike traditional monitoring which typically tracks basic metrics like uptime and system health, observability provides a much deeper understanding of how systems are functioning and why. It enables businesses to not only detect issues but also diagnose the root causes, empowering data-driven decisions that improve performance across the organisation.

Converting raw data into insightful knowledge is vital in a world where companies need to function more quickly and efficiently. Beyond simply detecting issues, observability’s power lies in its ability to help organisations foresee problems before they cause operational disruptions. This proactive strategy helps businesses maintain uptime, optimise resources, and, ultimately, deliver superior customer experiences.

The rise of AI-powered observability

As organisations grapple with increasingly complex hybrid IT environments, AI-powered observability has emerged as a cornerstone of innovation. These solutions go beyond ensuring uptime-they provide actionable intelligence that enables businesses to optimise IT operations and address challenges proactively.  With 68% of organisations leveraging AI tools for anomaly detection, root cause analysis, and real-time threat detection, the demand for advanced observability tools is surging. This trend reflects a growing recognition that these tools are no longer just a technical necessity but a strategic enabler of business success. Observability empowers enterprises to stay ahead by driving efficiency, resilience, and adaptability in an ever-evolving digital landscape. 

The path ahead: The convergence of AI and observability

As we approach 2025, businesses harnessing AI-powered observability are poised to gain a significant competitive edge over those still relying on traditional monitoring solutions. This shift is underscored by the fact that 81% of enterprises plan to boost their AI investments in the coming year focusing on predictive analytics, automation, and anomaly detection to further optimise data centers and support AI-driven innovation. The integration of AI with observability is not just about identifying problems – it’s about enabling businesses to anticipate challenges, enhance operations, and sustain a competitive edge.

For LogicMonitor, the coming year is about driving innovation in an industry that’s evolving as fast as our customers’ needs. By working closely with our clients like TopGolf and Franke, we’re helping them navigate this transformation with confidence. As observability technology becomes increasingly essential, we’re committed to empowering businesses to thrive without being held back by technological limitations.

Observability’s ever-more-important role in 2025

As 2025 approaches, observability is set to become even more integral to IT operations, compliance, and innovation. Regulations like the EU’s Digital Operational Resilience Act (DORA) which mandates robust ICT risk management and incident reporting for financial services,highlight the critical need for continuous observability throughout the development cycle. This shift will accelerate the adoption of Observability-Driven Development (ODD), a strategic approach to managing the complexities in distributed systems and microservices architectures.

The expansion of observability is driven by the increasing necessity to monitor applications, infrastructure, and services across diverse and dynamic environments while staying resilient and improving customer experience. As data volumes grow, organisations will face increased scrutiny over observability spending, making it even more crucial that they align with regulation to enhance operational resilience and compliance. AI-powered observability systems will continuously learn from new data, user feedback, and past incidents, allowing them to improve over time and become more accurate and effective at identifying anomalies, reducing noise, and pinpointing root causes.

One thing is clear as the observability landscape develops further: businesses that make investments in cutting-edge, AI-powered observability solutions will be better prepared to meet tomorrow’s problems and thrive in the rapidly shifting digital economy.

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