Category: 3. Business

News Summary:

• NVIDIA and Lilly bring together a world-leading, multidisciplinary team of scientists, AI researchers and engineers to address the hardest problems in drug discovery.
• The co-innovation lab infrastructure will be built on the NVIDIA BioNeMo platform and the NVIDIA Vera Rubin architecture.
• NVIDIA and Lilly will pioneer robotics and physical AI to accelerate and scale medicine discovery and production.

J.P. Morgan Healthcare Conference—NVIDIA and Eli Lilly and Company today announced a first-of-its-kind AI co-innovation lab focused on applying AI to tackle some of the most enduring challenges in the pharmaceutical industry.

The lab brings together Lilly’s world-leading expertise in discovering, developing and manufacturing medicines with NVIDIA’s leadership in AI, accelerated computing and AI infrastructure. The two companies will invest up to $1 billion in talent, infrastructure and compute over five years to support the new AI co-innovation lab.

Based in the San Francisco Bay Area, the lab will co-locate Lilly domain experts in biology, science and medicine with top AI model builders and engineers from NVIDIA, allowing them to work side by side to generate large-scale data and build powerful AI models that can accelerate medicine development, using NVIDIA BioNeMo™ as the critical platform.

“AI is transforming every industry, and its most profound impact will be in life sciences,” said Jensen Huang, founder and CEO of NVIDIA. “NVIDIA and Lilly are bringing together the best of our industries to invent a new blueprint for drug discovery — one where scientists can explore vast biological and chemical spaces in silico before a single molecule is made.”

“For nearly 150 years, we’ve been working to bring life-changing medicines to patients,” said David A. Ricks, chair and CEO of Lilly. “Combining our volumes of data and scientific knowledge with NVIDIA’s computational power and model-building expertise could reinvent drug discovery as we know it. By bringing together world-class talent in a startup environment, we’re creating the conditions for breakthroughs that neither company could achieve alone.”

Building a Continuous Learning System for Drug Discovery

The collaboration will initially focus on creating a continuous learning system that tightly connects Lilly’s agentic wet labs with computational dry labs, enabling 24/7 AI-assisted experimentation to support biologists and chemists. This scientist-in-the-loop framework aims to enable experiments, data generation and AI model development to continuously inform and improve one another.

Harnessing access to unprecedented compute for the industry, massive, high-quality data generation and NVIDIA BioNeMo as the platform to accelerate drug discovery, the teams will focus on building next-generation foundation and frontier models for biology and chemistry.

The new initiative expands on Lilly’s previously announced AI supercomputer and intends to harness investments in next-generation NVIDIA architectures, including NVIDIA Vera Rubin.

The AI factory Lilly announced last fall, which is the most powerful in the pharmaceutical industry, will train large biomedical foundation and frontier models for identifying, optimizing and validating new molecules with exceptional speed and accuracy. It will also support new and advanced applications in manufacturing, medical imaging and scientific AI agents.

Beyond drug discovery, NVIDIA and Lilly will explore opportunities to apply AI across clinical development, manufacturing and commercial operations to integrate multimodal models, agentic AI, robotics and digital twins.

The use of physical AI and robotics in the AI factory will also help Lilly enhance its capacity to manufacture high-demand medications and strengthen supply chain reliability. With NVIDIA Omniverse™ libraries and NVIDIA RTX PRO™ Servers, Lilly can create digital twins of its manufacturing lines to model, stress test and optimize entire supply chains before making physical changes in the real world.

Supporting Global Leadership in Biomedical Discovery

NVIDIA leads in open-source AI, empowering companies with the models, data and tools needed to develop real-world AI systems. In addition, the NVIDIA Inception program provides startups with access to technical mentorship, as well as NVIDIA software and compute.

Lilly TuneLab, an AI and machine learning platform, provides biotech companies with access to select Lilly models for drug discovery built on decades of Lilly’s proprietary data. TuneLab will include NVIDIA Clara™ open foundation models for life sciences as part of a future workflow offering.

The co-innovation lab will provide NVIDIA and Lilly’s startup ecosystems and researchers with deep expertise and scale of computing resources.

The lab’s work is expected to begin in South San Francisco early this year.

Like 2024 when the it shipped the most smartphones globally, Apple has maintained its streak of shipping the most smartphones in 2025 as global smartphone shipments rose by 2% year-on-year in 2025.

The slight uptick in phone sales are largely driven by stronger demand and economic growth in emerging markets, Reuters reported, citing data issued by Counterpoint Research.

The iPhone maker maintained its position as the market leader with a 20% share in 2025, the highest among the top five brands.

This landmark feat is courtesy of robust demand in major and mid-sized mobile phone markets and strong sales of the iPhone 17 series, as noted by analyst Varun Mishra.

Manufacturers advanced shipments early in the year to avoid tariffs, but the impact remained negligilbe as 2025 came to a close, leaving volumes in the second half largely unaffected.

Samsung managed at the second position with a 19% share after seeing modest growth in shipments, while Xiaomi came third with a 13% share, backed by consistent demand in emerging markets.

But the upward trend seems to have run its course as the global smartphone market is projected to collapse in 2026 due to chip shortages and rising component costs.

Counterpoint’s Research Director Tarun Pathak suggested that chipmakers are increasingly prioritising AI data centres over smartphone production, a move believed to adversely affect smartphone availability in 2026.

As the market is aligning strategies with challenges at hand, smartphone makers might need to reassess their approaches to maintain growth and meet consumer demands. 

• ABB’s integrated power, propulsion and control solution has been chosen for BC Ferries’ four new hybrid-electric major vessels
• The New Major Vessels have been designed to minimize emissions and underwater radiated noise (URN), with the goal of contributing to quieter and cleaner operations in the Strait of Georgia

ABB will supply a complete package of power, propulsion and control technology for four new double-ended passenger and car ferries operated by British Columbia Ferry Services (BC Ferries). One of the largest ferry operators in the world, BC Ferries provides year-round vehicle and passenger service on 25 routes to 47 terminals, carrying approximately 9.7 million vehicles and 22.7 million passengers annually ¹. Demand on the ferry system is expected to increase as the province’s population is forecast to grow 44 percent² by 2046.

The hybrid-electric ferries, which will replace four end-of-life vessels, are part of the BC Ferries’ New Major Vesselsprogram, aimed at delivering safe, environmentally sustainable and reliable operations in and around the Strait of Georgia, the body of water separating Vancouver Island from the Lower Mainland of British Columbia. The order was booked in the fourth quarter of 2025.

Scheduled for delivery beginning in 2029 from China Merchants Industry Weihai (CMI Weihai) Shipyard, the vessels will be equipped with ABB’s gearless, steerable Azipod® electric propulsion.The system offers proven reliability thanks to significantly fewer moving parts than mechanical thrusters, while the special propeller design helps reduce underwater radiated noise (URN). This helps safeguard at-risk species, such as the Southern Resident killer whale, and preserve one of the world’s most biologically rich marine ecosystems³.

ABB’s Onboard DC Grid™ power distribution system will serve as the backbone for efficient energy flow, minimizing conversion losses and enabling higher overall system efficiency and lower emissions than comparable propulsion arrangements.

Each ferry will be equipped to accommodate up to 70 megawatt-hours (MWh) of battery energy storage. This enables efficient hybrid operations today and supports a future shift to fully electric, zero-emission service. The hybrid configuration uses biofuel or renewable diesel and continuously balances energy between generators and batteries. Each vessel can also connect to a high-capacity shore charging system rated above 60 megawatts (MW) for full electric operation. This system is more than 100 times more powerful than the fastest public electric vehicle charging stations in North America, which typically deliver up to 500 kilowatts (kW) per plug. This high-capacity charging supports fast turnaround in port and enables the transition to zero-emission operations.

ABB’s digital solutions will give crews a clear overview of ship operations and support safe, efficient journeys. These digital technologies are intended to help BC Ferries deliver an improved travel experience for passengers while reducing environmental impact.

“BC Ferries’ New Major Vessels represent the largest capital investment in our history and are essential to renewing our fleet, increasing capacity on our busiest routes, and strengthening system resilience,” said Nicolas Jimenez, President & CEO, BC Ferries. “Their design reflects what our customers value most: comfort, accessibility and environmental stewardship. With diesel-battery hybrid technology that can operate on bio and renewable diesel today and transition to full electrification as infrastructure evolves, these ships are a critical part of building a cleaner, quieter, and more reliable ferry system for the future.”

“We proudly support BC Ferries’ goals to reduce greenhouse gas emissions from their operations, striving to meet British Columbia’s 2030 greenhouse gas emissions reduction target for the transportation sector⁴ by at least 27 percent by 2030, from 2008 levels, in support of a cleaner future for British Columbia, and its ambitions to transition to all-electric operation,” said Rune Braastad, President, ABB’s Marine & Ports division. “ABB’s deep roots in Canada make it possible to support generational infrastructure projects like the New Major Vessels.”

“Winning the contract to deliver such a wide scope of solutions is highly significant for ABB’s marine business in North America,” said Timo Vesala, Head of Sales, Marine Systems, Americas, ABB’s Marine & Ports division. “As someone who lives and works in Vancouver, I recognize the importance of this initiative for British Columbia – not only in providing consistently reliable and resilient ferry services, but also in helping local communities experience cleaner air and quieter waterways.”

ABB is a global technology leader in electrification and automation, enabling a more sustainable and resource-efficient future. By connecting its engineering and digitalization expertise, ABB helps industries run at high performance, while becoming more efficient, productive and sustainable so they outperform. At ABB, we call this ‘Engineered to Outrun’. The company has over 140 years of history and around 110,000 employees worldwide. ABB’s shares are listed on the SIX Swiss Exchange (ABBN) and Nasdaq Stockholm (ABB). www.abb.com

[1] British Columbia Ferry Services Inc. Annual Report to the British Columbia Ferries Commission – Year ended March 31, 2025.

[2] https://www.bcferries.com/in-the-community/projects/new-major-vessels

[3] https://georgiastrait.org/issues/about-the-strait-2/

[4] https://www.bcferries.com/web_image/hf0/hce/8910527397918.pdf

All cells within a multicellular organism have the same genetic sequence up to a minuscule number of somatic mutations. Yet, many cell types exist with diverse morphological and functional traits. Epigenetics is an important regulator and driver of this diversity by allowing differences in cellular state and gene expression despite having the same genotype (Taherian Fard and Ragan, 2019). Indeed, cells traversing the trajectory from pluripotency through terminal differentiation have essentially the same genotype.

Epigenetic modifications such as post-translational modifications (PTMs) to histone proteins are involved in many vital regulatory processes influencing genomic accessibility, nuclear compartmentalization, and transcription factor binding and recognition (Reik et al., 2001; Kouzarides, 2007; Gibney and Nolan, 2010; Klemm et al., 2019; Hafner and Boettiger, 2023; Zhang and Reinberg, 2001). The Histone Code Hypothesis suggests that combinations of different histone PTMs specify distinct chromatin states, thereby regulating gene expression (Strahl and Allis, 2000; Jenuwein and Allis, 2001).

The field of epigenome editing has produced new tools for understanding the outcomes of epigenetic perturbations that promise to be useful for therapeutics by enabling fine-tuned control of gene expression (Matharu and Ahituv, 2020; Thakore et al., 2016; Goell and Hilton, 2021; Stricker et al., 2017). Currently, small molecule drugs are used to potently interfere with epigenetic regulation of gene expression. For example, Vorinostat inhibits histone deacetylases, thereby impacting the epigenetic landscape (Estey, 2013; Yoon and Eom, 2016). However, small molecules globally disrupt the epigenome and transcriptome and therefore are not suitable for targeting individual dysregulated genes nor clarifying epigenetic regulatory mechanisms (Swaminathan et al., 2007). Meanwhile, numerous tools have been designed to harness catalytically dead Cas9 (dCas9) to target epigenetic modifiers to DNA sequences encoded in guide RNAs (gRNAs) (Jinek et al., 2012; Mali et al., 2013; Hilton et al., 2015; Stepper et al., 2017; Kwon et al., 2017; Li et al., 2021). CRISPR-Cas9-based epigenome editing strategies facilitate unprecedented, precise control of the epigenome and gene activation, providing a path to epigenetic-based therapeutics (Cheng et al., 2019).

A major challenge for epigenome editing is designing gRNAs that can achieve a desired level of transcriptional or epigenetic modulation. Finding effective gRNAs currently typically requires expensive and low-throughput experimental strategies (Mohr et al., 2016; Liu et al., 2020; Mahata et al., 2023). An alternative approach would be to computationally model how epigenome editing impacts histone PTMs as well as how perturbing these PTMs would consequently impact gene expression.

To understand how histone PTMs relate to gene expression, large epigenetic and transcriptomic datasets are required. Advancements in high-throughput sequencing have allowed quantification of gene expression and profiling of histone PTMs. Large consortia have performed an extensive number of assays across a wide variety of cell types (The ENCODE Project Consortium, 2012; Kundaje et al., 2015; Barrett et al., 2012).

These include measurements of histone PTMs, transcription factor binding, gene expression, and chromatin accessibility. These data have enhanced our understanding of how histone PTMs and other chromatin dynamics impact transcriptional regulation (Keung et al., 2015; Rao et al., 2014; Holoch and Moazed, 2015).

Studying the function of these histone PTMs, however, has been largely limited to statistical associations with gene expression, which may not capture causal relationships (Karlić et al., 2010; Stillman, 2018; Singh et al., 2016). For example, deep learning has been successful in predicting gene expression from epigenetic modifications, such as transcription factor binding (Schmidt et al., 2017), chromatin accessibility (Schmidt et al., 2020), histone PTMs (Singh et al., 2016; Sekhon et al., 2018; Frasca et al., 2022; Singh et al., 2017; Hamdy et al., 2022; Chen et al., 2022), and DNA methylation (Zhong et al., 2019). However, these studies predict gene expression as binary levels instead of a continuous quantity. Finally, as statistical associations can be driven by non-causal mechanisms, it is unclear whether such computational models learn mechanistic, causal relationships between various epigenetic modifications and gene expression. Beyond modeling the relationship between histone PTMs and gene expression, to fully describe how a particular gRNA would affect gene expression, a model of how epigenome editing affects histone PTMs is also required. To our knowledge, there currently are no computational models that can accurately model, in silico, the impact of epigenome editing on histone PTMs.

Motivated by these observations, we explored models for how epigenome editing impacts histone PTMs as well as how histone PTMs impact gene expression. We used data available through ENCODE (Schreiber et al., 2020a; The ENCODE Project Consortium, 2012) to train a model of how histone PTMs impact gene expression. Our model is highly predictive of endogenous expression and learns an understanding of chromatin biology which is consistent with known patterns of various histone PTMs (Kimura, 2013). To test this model in the context of epigenome editing, we generated perturbation data using the dCas9-p300 histone acetyltransferase system (Hilton et al., 2015). The dCas9-p300 system is thought to act primarily through local acetylation of histone lysine residues, particularly histone subunit H3 lysine residue 27 (H3K27ac). Therefore, we modeled the impact of dCas9-p300 on the epigenome as a local increase in the H3K27ac profile near the target site; since the precise effect of these perturbations is unknown, we tried a variety of potential modification patterns. We then applied our trained model to predict the impact of these putative H3K27ac modifications on gene expression (Figure 1). We found that our models, which are designed to predict gene expression values, were effective in ranking relative fold-changes among genes in response to the dCas9-p300 system, achieving a Spearman’s rank correlation of ∼0.8. However, their performance in ranking fold-changes within individual genes was less successful when compared to the prediction of gene expression across cell types from their native epigenetic signatures. We offer possible explanations in the discussion section.

Long before the invention of writing, the very first detectable graphic productions of prehistoric humans were highly regular non-pictorial geometric signs such as parallel lines, zig-zags, triangular, or checkered patterns (Henshilwood et al., 2018; Waerden, 2012). Human cultures throughout the world compose complex figures using simple geometrical regularities such as parallelism and symmetry in their drawings, decorative arts, tools, buildings, graphics, and maps (Tversky, 2011). Cognitive anthropological studies suggest that, even in the absence of formal western education, humans possess intuitions of foundational geometric concepts such as points and lines and how they combine to form regular shapes (Dehaene et al., 2006; Izard et al., 2011). The scarce data available to date suggests that other primates, including chimpanzees, may not share the same ability to perceive and produce regular geometric shapes (Close and Call, 2015; Dehaene et al., 2022; Sablé-Meyer et al., 2021; Saito et al., 2014; Tanaka, 2007), though unintentional-but-regular mark-marking behavior has been reported in macaques (Sueur, 2025). Thus, studying the brain mechanisms that support the perception of geometric regularities may shed light on the origins of human compositionality and, ultimately, the mental language of mathematics. Here, we provide a first approach through the recording of functional MRI and magneto-encephalography signals evoked by simple geometric shapes such as triangles or squares. Our goal is to probe whether, over and above the pathways for processing the shapes of images such as faces, places, or objects, the regularities of geometric shapes evoke additional activity.

The present brain-imaging research capitalizes on a series of studies of how humans perceive quadrilaterals (Sablé-Meyer et al., 2021). In that study, we created 11 tightly matched stimuli that were all simple, non-figurative, textureless four-sided shapes, yet varied in their geometric regularity. The most regular was the square, with four parallel sides of equal length and four identical right angles. By progressively removing some of these features (parallelism, right angles, equality of length, and equality of angles), we created a hierarchy of quadrilaterals ranging from highly regular to completely irregular (Figure 1A). In a variety of tasks, geometric regularity had a large effect on human behavior. For instance, for equal objective amounts of deviation, human adults and children detected a deviant shape more easily among shapes of high regularity, such as squares or rectangles (<5% errors), than among irregular quadrilaterals (>40% errors). The effect appeared as a human universal, present in preschoolers, first-graders, and adults without access to formal western math education (the Himba from Namibia), and thus seemingly independent of education and of the existence of linguistic labels for regular shapes. Strikingly, when baboons were trained to perform the same task, they showed no such geometric regularity effect.

Baboon behavior was accounted for by convolutional neural network (CNN) models of object recognition, but human behavior could only be explained by appealing to a representation of discrete geometric properties of parallelism, right angle, and symmetry, in this and other tasks. We sometimes refer to this model as ‘symbolic’ because it relies on discrete, exact, rule-based features rather than continuous representations (Sablé-Meyer et al., 2022). In this representational format, geometric shapes are postulated to be represented by symbolic expressions in a ‘language-of-thought’, for example ‘a square is a four-sided figure with four equal sides and four right angles’ or equivalently by a computer-like program from drawing them in a Logo-like language (Sablé-Meyer et al., 2022).

We therefore formulated the hypothesis that, in the domain of geometry, humans deploy an additional cognitive process specifically attuned to geometric regularities. On top of the circuits for object recognition, which are largely homologous in human and non-human primates (Bao et al., 2020; Kriegeskorte et al., 2008b; Tsao et al., 2008), the human code for geometric shapes would involve a distinct ‘language of thought’, an encoding of discrete mathematical regularities and their combinations (Cavanagh, 2021; Dehaene et al., 2022; Fodor, 1975; Leeuwenberg, 1971; Quilty-Dunn et al., 2022; Sablé-Meyer et al., 2022; Sablé-Meyer et al., 2021).

This hypothesis predicts that the most elementary geometric shapes, such as a square, are not solely processed within the ventral and dorsal visual pathways, but may also evoke a later stage of geometrical feature encoding in brain areas that were previously shown to encode arithmetic, geometric, and other mathematical properties, that is the bilateral intraparietal, inferotemporal, and dorsal prefrontal areas (Amalric and Dehaene, 2016; Amalric and Dehaene, 2019). We hypothesized that (1) such cognitive processes encode shapes according to their discrete geometric properties including parallelism, right angles, equal lengths, and equal angles; (2) the brain compresses this information when those properties are more regularly organized, and thus exhibit activity proportional to minimal description length (Chater and Vitányi, 2003; Dehaene et al., 2022; Feldman, 2003); and (3) these computations occur downstream of other visual processes, since they rely on the initial output of visual processing pathways.

Here, we assessed these spatiotemporal predictions using two complementary neuroimaging techniques (functional MRI and magnetoencephalography [MEG]). We presented the same 11 quadrilaterals as in our previous research and used representational similarity analysis (Kriegeskorte et al., 2008a) to contrast two models for their cerebral encoding, based either on classical CNN models or on exact geometric features. In the fMRI experiment, we also collected simpler images contrasting the category of geometric shapes to other classical categories such as faces, places, or tools. Furthermore, to evaluate how early the brain networks for geometric shape perception arise, we collected those fMRI data in two age groups: adults and children in first grade (6 years old, this year was selected as it marks the first year French students receive formal instruction in mathematics). If geometric shape perception involves elementary intuitions of geometric regularity common to all humans, then the corresponding brain networks should be detectable early on.

A new AI breakthrough could slash the time it takes to discover life-saving medicines, according to researchers in China.

Scientists at Tsinghua University have developed a powerful system called DrugCLIP, which can screen drug molecules against human proteins at staggering speed compared to traditional drug-testing methods.

According to Physics.org, DrugCLIP uses deep contrastive learning to convert both drug molecules and protein binding pockets into digital vectors, allowing the system to match them almost instantly.

The AI screened 500 million molecules across 10,000 human proteins in testing, covering around half of the human druggable proteome.

Researchers say the system carried out 10 trillion molecule–protein evaluations in a single day, making it around 10 million times faster than classic docking simulations, which are commonly used in early drug discovery.

To build the platform, the team used AlphaFold2 to generate protein structures and refined the binding sites with a custom tool called GenPack. The results were then validated using both computer modelling and laboratory experiments.

In their paper, the scientists said: “DrugCLIP is an ultrafast virtual screening method that we rigorously validated through in silico benchmark evaluation and wet-lab experiments.”

They added, “Its speed enables trillion-scale screening covering the human druggable proteome, providing an open-access resource that forms a foundation for next-generation drug discovery, particularly for less understood targets.”

Notably, the AI identified potential compounds for TRIP12, a protein linked to cancer and autism that has so far resisted traditional drug-targeting efforts.

All of DrugCLIP’s data and models are freely available, meaning laboratories around the world can now use the system to dramatically speed up early-stage drug development.

Researchers have identified four new business models for the era of agentic artificial intelligence:

• Existing+. Augment an existing business model with AI.
• Customer Proxy. Achieve customer outcomes through predefined processes executed by AI.
• Modular Creator. Use AI to assemble reusable modules (including third parties) to assist in achieving customer outcomes, with no predetermined process.  
• Orchestrator. Achieve customer outcomes by using AI to assemble an ecosystem of complementary products and services, with no predetermined process.

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If your enterprise is pivoting amid a changing technology landscape, rest assured that you’re not alone. A recent research brief from the MIT Center for Information Systems Research  outlined how business models are evolving to keep pace with advances in artificial intelligence, and what it takes to successfully navigate change. 

The original digital business models 

To understand new business models for the AI era, it helps to unpack the old ones first. In 2013, MIT CISR researchers Peter Weill and Stephanie Woerner identified four digital business models:

1. Supplier companies, which sell products through third parties, like manufacturers.
2. Omnichannel companies, which have a digital and physical presence, such as retailers and banks.
3. Modular Producers, which offer plug-and-play products or services, such as payment service providers.
4. Ecosystem Drivers, which offer a go-to destination in a given customer domain (e.g., housing) and connect customers with providers. 

These models have seen significant shifts in the past 12 years, with companies that lead or otherwise participate in a digital ecosystem becoming far more prevalent than traditional brick-and-mortar sellers. Focusing on firms’ dominant models, supplier and omnichannel business models are much less prevalent today, while companies with ecosystem driver business models have grown from 12% of businesses in 2013 to 58% of businesses in 2025. In large part, this is because these companies were the only ones of the four to exceed industry-average revenue growth. 

These shifts, coupled with rapid adoption of AI in all its forms — machine learning plus agentic, generative, and robotic AI — prompted the development of a new business model framework.  

4 business models for the AI era 

For the update, Weill, Woerner, and colleagues Ina Sebastian and Gayan Benedict used survey data obtained from 2,378 companies between 2013 and 2025 to organize business models into four new categories. They used the example of a hypothetical financial services company to describe how the business models operate in theory.

• Existing+: These firms augment an existing business model with AI. Here, a financial services company could enhance the traditional advisory process by using AI to analyze customer information and provide personalized recommendations.
• Customer Proxy: These firms achieve customer outcomes (within guardrails) using predefined processes now supported by AI. In this case, a financial services company could set parameters to automatically manage a customer’s investment portfolio.
• Modular Creator: Much like producers of plug-and-play products, these firms use AI to assemble reusable modules (including those from third parties) into tailored service bundles. Applying this model, a financial services company could create and recommend a bundle of investment, insurance, and credit products that align with a customer’s goals.
• Orchestrator: These firms achieve customer outcomes (within guardrails) by using AI to assemble an ecosystem of complementary products and services. In this case, a financial services company could provide a fully managed wealth solution that automatically and continuously optimizes the customer’s investment portfolio.

How One New Zealand Group has evolved its business model 

The ongoing transformation of telecommunications provider One New Zealand Group illustrates these business models in action. Currently, for example, the company uses AI agents to help answer customers’ frequently asked questions and assist employees in serving customers (the Existing+ model); act on requests to upgrade plans or create service tickets (Customer Proxy); and monitor power failures, forecast demand, and recommend action during weather-related service disruptions (Modular Curator). 

Looking ahead, One NZ intends to bring autonomous AI agents to marketing operations (Orchestrator). Agents would be capable of creating personalized campaigns and adapting them based on how customers respond. The marketing team would set goals and guardrails for the AI agents and monitor their performance.

Companies seeking to adapt the way that One NZ has need to understand where they can create value, according to the researchers. Does your company merely assist customers, or can it represent their goals through autonomous action? Is business execution built on a structured process, or can that process be adapted, with the help of AI agents, based on a customer’s desired outcomes? 

Leaders looking to understand the opportunities AI offers their company can start by identifying existing AI-enabled business models that they can scale, and the corresponding AI capabilities a company needs to build.

Read the research briefing: “Business models in the AI era“

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This article is based on research by Peter Weill, Ina Sebastian, Stephanie Woerner, and Gayan Benedict from the MIT Center for Information Systems Research. 

Peter Weill is a senior research scientist at MIT Sloan and chairman of MIT CISR. His work explores future trends, such as digital business models, IT investment portfolios, and AI maturity models, to help organizations maintain a competitive edge. Ina Sebastian is a research scientist at MIT CISR. She studies how large enterprises transform for success in the digital economy, with a focus on digital partnering, value creation, and value capture in digital models. Stephanie Woerner is a principal research scientist at MIT Sloan and the director of MIT CISR. She studies how companies use technology and data to make more effective business models, as well as how they manage associated organizational change, governance, and strategy implications. Gayan Benedict is an industry research fellow at MIT CISR and a technology partner at PwC Australia.  

Krystle Sampani-Morales is used to people calling her “Ma’am K” – even Sandvik customers who use it affectionately when they call and ask her for help solving a variety of issues.

Sampani-Morales was recruited to Sandvik ten years ago as a customer service representative in the Philippines. She was increasingly given additional responsibility from mentors who believed in her capabilities and gave her the independence and freedom to do what needed to be done – and that is still the case in her job today.

A trusted problem-solver

Now, as the Sales Support Team Lead, Sampani-Morales is based at the Mining office in Manila but also spends some time on the road visiting customers on mining sites to clarify processes, handle parts and rock tool inquiries, ensure staff understands the contract on site, or train staff for continuous learning. She’s become something of an expert when it comes to quick problem solving, working with logistics, inventory, and warehouse teams to ensure customers get the parts they need. “I don’t know what my job description is anymore!” says Sampani-Morales, adding that she continues to learn on the job.

Prior to Sandvik, she worked in sales administration as a supervisor, handling customer orders for Johnson & Johnson. She has a Bachelor of Science degree in Computer Science from Polytechnic University of the Philippines, which comes in handy too, particularly with the Sandvik systems. Colleagues and customers rely on her regularly for system support and training.

Sandvik is very passionate about customer satisfaction, and we don’t want people to feel alone. We promote inclusivity among our team members. They should know they have processes and team support.

Sampani-Morales also appreciates the Sandvik culture of building strong, lasting relationships with its customers – and how the Filipino values are embraced locally. “We support our customers on their low days too,” she points out explaining that when one company encountered a short-term financial issue, they were met with understanding from Sandvik and an extension. “That business eventually grew and the company is today one of the best mining companies in the Philippines – and a major Sandvik customer.”

Perhaps the biggest challenge for Sampani-Morales initially was being on a mining site, something she felt nervous about at first. The strict safety regulations and thorough training at customer mines quickly put her mind at ease. Today she travels long distances to the north and south of the Philippines to gold, copper and nickel mines like Oceanagold in Luzon, Filminera in Masbate, and Apex Mining in Davao, which is nearly 1,500 kilometers from her home in Manila.

From office to mine site

Visiting a mine approximately once a month has given her invaluable insights for her role. “I have learned so much about mining and I have big respect for colleagues at the mines. After visiting mining sites, I understand why everything is so urgent. The mines are working 24/7 and if a machine is down, their production is down.”

As a hiker, surfer and nature lover, Sampani-Morales initially questioned whether mining was an appropriate field for her to work in. She soon came to realize “there is a difference between good mines and bad ones,” and was comforted by the fact that Sandvik only conducts business with the “good ones” – fully compliant customers.

“These are mining customers who prioritize and promote safety, follow all regulations and standards of the government and ensure environmental protection,” she explains. “It’s important to also understand that mining is not about destroying our environment but providing essential minerals and metals.”

Balancing career and family

Outside of work, this wife and mother of two young boys prioritizes family, and she looks forward to the day when her seven and two-year-old sons are old enough to go on the weekend hiking and surfing trips that she’s eager to resume.

Back at the office, one of the best things about the daily work is having good colleagues, she says. “We share our lunches together and laugh all the time!”

And for those considering a career within Sandvik, Sampani-Morales has some final words: “You get to be independent – and work with a team – and you learn a lot every day.”

A “lifeline” flight service between Wick and Aberdeen will resume on Wednesday after the subsidised air service stopped in October.

The previous operator, Eastern Airways, entered administration in November, forcing Highland Council to launch an emergency procurement process.

Air Charter Scotland will run the service six days a week using an 18-seat Jetstream 32 aircraft.

The local authority and Scottish government fund the public service obligation (PSO) route. Highland Council has said it is exploring the option of extending the contract to include flights from Wick to Edinburgh.