6 Companies Leading the AI Transformation in Organisations

Learn how companies such as Ericsson, Abpro, and Hexagon are using AI to do amazing things, like making things work better, keeping people safe, and helping people get better

Glenn Burgess

Learn how companies like Ericsson, Abpro, and Hexagon are using AI to do amazing things, like making tasks easier, keeping people safe, and improving people’s lives.

Generative AI is changing the way we work, saving time, enabling people to do things they couldn’t do before, and creating new opportunities. However, there are concerns. Workers worry that their jobs might be replaced by lower-quality, cheaper AI-generated work.

Another issue is accuracy. Generative AI systems often make mistakes, and if people rely on them too much, they may stop checking the results.

Generative AI is just one part of AI being used today. We talked to several executives through email and selected six stories that show different ways AI is already making a difference. These six companies are using AI to change how things are done in their industries, leading to better efficiency, safety, customer experiences, and innovations.

The executives from these companies shared how they use AI, how it has changed their processes, and the benefits they’ve seen. We want to thank them for their time and detailed responses.

Ericsson: Transforming Telecommunications with AI

Ericsson Safe Work, a part of the telecommunications giant Ericsson, is making telecommunications safer with AI. According to Vivek Gnanavelu, the founder and CEO of Ericsson Safe Work, their goal is to protect the lives of telecom workers.

In the telecommunications industry, especially when it comes to tasks like installing or maintaining cell towers, accidents can happen despite safety measures. Gnanavelu mentions that they’ve achieved significant efficiencies using AI. These efficiencies include saving crew time, detecting non-compliance with safety standards through AI, and improving the approval process for safety forms.

The company employs computer vision and AI to make sure workers are following safety rules, such as wearing helmets, gloves, vests, and work boots. They also provide real-time weather alerts and risk assessments. AI continuously monitors vital signs to ensure workers are fit for their tasks.

On a broader scale, the company uses AI pattern recognition to automate reporting and analyse large amounts of data. This helps them learn from past incidents and prevent similar accidents in the future.

SoFi: Using AI to Transform Banking

SoFi is a digital financial services provider that aims to help over six million members achieve financial independence. According to Aaron Webster, the Chief Risk Officer and Global Head of Operations in Latin America, SoFi employs an advanced AI solution that goes beyond traditional chatbots.

It utilises an intelligent digital assistant model capable of understanding customer emotions, leading to improved customer experiences. This AI assistant utilises advanced natural language processing, providing interactions similar to human conversations, adapting in real-time, seamlessly transitioning to human agents when necessary, and delivering personalised responses.

SoFi has integrated Cyberbank Konecta, a conversational AI engine from Galileo Financial Technologies affiliates, into their technology infrastructure. This integration enhances member experiences by offering automated assistance outside regular customer support hours.

Webster explains that they use conversational AI with empathy to customise each member interaction on the spot. This approach adds a human touch when needed while also reducing operational service costs by efficiently handling common inquiries with AI.

Since implementing this solution, SoFi has achieved a 65% improvement in response times, and significantly fewer customers abandon chat interactions. Thousands of conversations are now successfully resolved without the need for transfer to a human agent.

Hexagon: Advancing Public Safety with AI

Hexagon AB, headquartered in Stockholm, is a multinational company with a €5.2 billion valuation, focusing on serving municipalities. According to Kalyn Sims, the Chief Technology Officer for Hexagon’s Safety, Infrastructure & Geospatial division, real-time data intelligence is crucial, and assistive AI plays a vital role in managing the vast amounts of data available today.

Assistive AI helps human operators process large volumes of data by identifying patterns, correlations, or anomalies that might be challenging or time-consuming for a person to spot.

Hexagon’s Safety, Infrastructure & Geospatial division enhances the resilience and sustainability of critical services and infrastructure. Their technologies transform complex data into meaningful insights, enabling faster and better decision-making in areas such as public safety, utilities, defense, transportation, and government.

Assistive AI, as described by Sims, ensures that agencies can make the most of real-time data before it becomes irrelevant. It uses advanced statistics and machine learning to detect immediate action items within an organisation’s operational data.

For instance, assistive AI assists police, fire, and EMS in identifying and responding to complex emergencies more efficiently. It operates in the background, aiding 911 dispatchers by recognising patterns and determining connections between public safety events. It alerts dispatchers to anomalies, leaving the decision-making about resource allocation to humans.

The public safety sector is high-stress, and it faces staffing challenges. With a growing number of public service calls and data from various sources like surveillance cameras, traffic sensors, and IoT devices, users can become overwhelmed.

Sims suggests that new collaborative AI capabilities can alleviate this problem. These smart technologies integrate with existing systems, easing the workload for crime analysts and dispatchers by analysing incoming real-time data, identifying trends and anomalies, and delivering instant alerts.

According to Sims, this autonomous initial assessment achieved through assistive AI technology is more efficient, effective, and scalable than manual monitoring and analysing information from multiple sources, including calls from the public, sensors, and alarms.

Revolear: AI Revolutionising B2B Sales

Revolear specialises in providing tools for intricate B2B sales processes. According to Founder and CEO Raja Singh, it offers a state-of-the-art digital deal platform infused with AI that revolutionises how companies handle complex business solutions, from structuring to proposing, negotiating, and approving.

AI plays a significant role in both Revolear’s product and its development process. In the realm of B2B sales, which can often span months with numerous complexities, there are various opportunities to leverage AI.

Revolear uses generative AI to distill customer requirements and generate personalised sales proposal text tailored to different roles. They employ machine learning to predict the most suitable discount levels and other deal terms, as well as to create metrics that gauge deal momentum and approval probabilities.

In their development efforts, Revolear’s team utilises GitHub’s Copilot tools to assist with coding. Singh emphasises that AI doesn’t replace engineers but can help complete lines of code or contribute code snippets. Additionally, they use generative AI to enhance their marketing copy, proofreading & improving sections.

An especially valuable application is generating fictitious demo data, which enhances their product presentations with realistic information, and ChatGPT can produce such data in large quantities.

Singh notes that AI has significantly reduced friction in one of the most challenging aspects of the sales process. Setting an initial asking price can be nerve-racking for sales teams, often relying on experience.

However, Revolear has developed machine learning models with minimal data (as few as 50 rows) to predict final prices, streamlining this critical decision-making process.

Abpro: AI in biopharmaceuticals

Abpro, a biotechnology firm specialising in monoclonal antibody therapies for cancer, eye care, and infectious diseases, has been at the forefront of COVID-19 treatment development. CEO and co-founder Ian Chan highlights the pivotal role of AI in combating the virus.

One persistent challenge with COVID-19 has been the rapid evolution of virus variants, often outpacing the development of treatments. Abpro addresses this issue by harnessing AI to predict changes in the virus’s spike protein and other regions.

This predictive capability enhances the future-proofing of treatments, allowing Abpro to stay ahead of evolving variants. AI combines tested biochemical data and real experimental results to train predictive models for antibodies.

AI has become an invaluable tool in identifying new drug targets, designing drugs, and accelerating the overall drug discovery process. It streamlines complex tasks, expediting the design and optimisation of antibodies.

Machine learning models are employed to enhance specific antibody properties, including binding affinity, solubility, immunogenicity, and yield. AI also predicts pathways for synthesising theoretical drug compounds and suggests modifications to simplify their production.

The time savings achieved with AI are substantial. Traditional monoclonal antibody discovery methods involved lengthy experimental processes. However, according to Chan, AI empowers biopharma companies like Abpro to condense an approximately eight-week experimental process into a single afternoon.

The Digital Panda: Unleashing AI in Creative Agencies

The Digital Panda, a small creative agency specialising in branding, web, mobile, and motion design, has integrated AI into its creative process. They rely on readily available cloud AI tools like Midjourney and ChatGPT to enhance their workflow.

Midjourney assists in swiftly generating high-quality storyboards for motion projects, while ChatGPT aids their development team with coding and bug fixing.

Ilya Kroogman, the founder of The Digital Panda, explains that they leverage Large Language Models (LLMs) to enhance their copywriting output and automate the process of sharing their work on various social platforms.

Kroogman further elaborates, “Using Midjourney has also enabled our creative team to significantly expedite the ideation phase for mood board and storyboard development. Previously, we spent hours on ideation, sketching, and conceptualisation, but now we can simply communicate our ideas to the model and iterate almost instantly.”

In essence, Kroogman attributes generative AI to transforming their organisation, making it feel and function as if it were much larger in scale.

AI-Driven Organisational Transformation

Executives are sharing their perspectives on the rapid adoption of generative AI within organisations. Jiani Zhang, Executive Vice President and Chief Software Officer of Capgemini Engineering, the parent company of Capgemini, a multinational IT services and consulting firm, acknowledges the intrigue surrounding generative AI as a relatively new technology.

Many companies are experimenting with generative AI due to its potential to accelerate use cases across various areas like knowledge management, support, and code generation. However, Zhang highlights that adoption levels vary, primarily due to concerns about the reliability of the generated content.

Zhang provides three recommendations for organisations looking to incorporate AI:

Establish new processes to address regulatory and ethical aspects of AI development, especially concerning code generation.
Ensure trust in the generated content by validating the integrity of large language models (LLMs) used.
Implement new processes during the development lifecycle to validate the generated content.

Meanwhile, Slalom, a global business and technology consulting company, conducted a survey of 200 C-suite executives across the US to understand their AI investments in 2023 and their sentiments for 2024.

The survey highlights the current use of AI within organisations and future directions. Interestingly, 71% of executives admit to not fully comprehending the scope of tasks that AI can augment or automate within their organisations.

These tasks span various sectors, including organisation and workforce, technology and data, business and customer value, strategy alignment and orchestration, and security, ethics, and governance. However, despite the lack of full understanding, 87% of executives have initiated AI adoption or transformation initiatives.

Tony Ko, Managing Director of Business Development and Advanced Analytics at Slalom Consulting, notes that most companies have already made AI investments, such as AI chatbots and internal training to improve employee workflows.

Yet, many struggle with the rapid pace of AI advancement and seek guidance to define long-term visions & necessary investments to stand out from competitors.

As a result, 70% of executives plan to increase resource allocation and budget allocation for AI in 2024. This underscores how AI is not merely an add-on but a transformative force driving change, reshaping industries, and expanding possibilities across both traditional and emerging sectors.

What does it all mean?

In 2024, AI’s Impact Will Go From Big to Huge”

Ali Minnick, Slalom’s General Manager of Global Business Advisory Services, predicts that while many companies hesitated to budget for large-scale AI transformation efforts in 2023 due to concerns about a possible recession, the landscape will change significantly in 2024.

Despite lingering economic uncertainties, the fear of falling behind in the AI race is prompting organisations to prepare to invest more heavily in AI.

Across the six spotlighted companies – Ericsson, SoFi, Hexagon, Revolear, Abpro, and The Digital Panda – several common themes emerge in their AI utilisation:

Enhanced Efficiency: Both SoFi and Hexagon leverage AI to expedite processes that were traditionally manual, resulting in faster customer service and quicker data processing for public safety, respectively.

Improved Decision-Making: Hexagon’s assistive AI provides valuable insights to public safety agencies, aiding them in making informed decisions that can prevent potential risks or threats.

Customer-Centric Solutions: SoFi enhances customer service through conversational AI, and Revolear optimises the B2B sales process to improve client experiences.

Safety and Compliance: Ericsson focuses on workplace safety, while Hexagon emphasises public safety and crime prevention through AI.

Innovation in Traditional Sectors: Abpro employs AI for drug discovery in the biopharmaceutical industry, and Ericsson applies AI in telecommunications, showcasing AI’s transformative potential in long-established sectors.

Adaptive Learning and Evolution: The Digital Panda utilises AI for rapid design mockups, demonstrating how AI-driven solutions can evolve and adapt to deliver better results over time.

Challenging the Status Quo: Companies like Revolear and Abpro use AI to redefine norms in their respective industries, from B2B sales to drug discovery.

Holistic Solutions: Ericsson’s comprehensive approach to worker safety, integrating AI, computer vision, and IoT, exemplifies a holistic use of technology to address complex issues.

In conclusion, these themes underscore the transformative power of AI across diverse sectors, from banking to biopharmaceuticals. AI is not just a trend; it has become an essential force for driving efficiency, safety, and innovation.

Kevin McClelland, General Manager of Slalom Build, aptly compares adopting generative AI to jumping on a moving train while blindfolded, emphasising the urgency and complexity involved.

It’s clear that the train is not stopping, and AI’s potential will continue to expand. Staying informed and making informed decisions is essential as we navigate this AI-driven future.