Healthcare transforms with a focus on accessibility, prioritizing IT, the global market is projected at USD 975 billion by 2027. AI and machine learning, expected in 90% of US hospitals by 2025, streamline chronic condition diagnoses. Emerging technologies drive change, influencing preventive and home care in the healthcare landscape.

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What’s inside

1. Key takeaways
2. Key drivers shaping trends in healthcare
3. Business trends driving innovation
4. Technology trends aiding the business

Key takeaways

Healthcare IT is a top priority for providers. Nearly 80% of healthcare providers consider it one of their top 5 strategic priorities, with investments in software including revenue cycle management, security and privacy, patient intake/flow, clinical systems, and telehealth. AI, ML, and IoMT are rapidly developing and expected to be used in 90% of US hospitals by 2025. The global mHealth apps market is growing, primarily driven by the adoption of fitness and medical apps. Technology can improve patient care, reduce medical errors, and expand hospital boundaries. However, data interoperability and regulations are necessary, and patient engagement is crucial for a better healthcare system. Download Complete Research

Key drivers shaping trends in healthcare

Empowering customers through GenAI

• Patient centricity is a top priority as patients now expect a satisfying healthcare experience, like what they receive in other industries. With technological advancements, it is now feasible and cost-effective to meet these expectations and provide patients with a superior experience.
• Healthcare data is vital for informed decision-making, and data integration is necessary to enable seamless sharing of information between healthcare providers. Seamless integration is vital for seamless patient care, coordinated care delivery, reducing errors, enhancing patient outcomes, and promoting a holistic approach to healthcare.
• Preventive healthcare is gaining importance as it reduces costs, improves quality of life, promotes early detection, and aligns with advancing healthcare technologies and government policies.

Business trends driving innovation

• The COVID-19 pandemic has accelerated the adoption of telehealth and telemedicine, leading to a significant growth of the global telemedicine market size.
• Retail healthcare services are gaining popularity due to their convenience and accessibility.
• However, the healthcare industry is facing challenges related to data security, cyberattacks, and lack of standardization, which can be tackled by upgrading cybersecurity infrastructure, conducting risk assessments, and complying with regulatory standards.
• mHealth apps are transforming healthcare by providing easy access to health monitoring, medication management, and wellness, while personalized medicine uses an individual’s genetic profile to inform disease prevention, diagnosis, and treatment.
• The use of AI-driven data interoperability is transforming healthcare data exchange, and regenerative medicine is encouraging regeneration and repair of damaged tissues and organs.
• Population health management involves analyzing healthcare data to monitor and enhance the health of each person within a population.
• These healthcare trends impact various stakeholders, including doctors, nurses, patients, pharmacists, and healthcare administrators.

Technology trends aiding the business

• Artificial intelligence (AI) is transforming healthcare by analyzing patient data, developing new drugs, and improving diagnoses.
• The global AI market for healthcare is projected to reach a significant amount by a certain year.
• Nanotechnology promises to revolutionize healthcare by enabling precise diagnosis, targeted drug delivery, and enhanced treatment options.
• The Internet of Medical Things (IoMT) and wearable devices are becoming increasingly popular for real-time monitoring, diagnosis, and therapy delivery.
• Robotics, digital twins, virtual reality, health data analytics, and gene editing are also promising in improving healthcare.
• However, ethical concerns regarding gene editing must be addressed, and regulatory frameworks must be updated to ensure responsible use

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Credits
Lead Authors@lab45: Anju James
Contributing Authors@lab45: Hussain S Nayak

Generative AI is forming a new economic ecosystem, reshaping the behaviour of key players in the IT industry, generating opportunities for super-scalers, and unveiling numerous niches for startups. The outlines of this new IT landscape are emerging, prompting a closer examination.

What's inside

1. Introduction: The rise & impact of generative AI
2. The technology & business stack of GenAI
3. Business niches for GenAI startups
4. Future trends in GenAI
5. Appendix 1: Reality & expectations of GenAI
6. Appendix 2: Startups across the GenAI tech stack

Introduction: The rise & impact of generative AI

Generative AI has caused significant disruption, expanding its offerings and services well beyond traditional AI domains. This has led to an explosion of potential use cases for customers who aren't AI experts. Unlike before, customers no longer require a team of AI experts, curated data, or precisely measurable outcomes to adopt AI tool and gain immediate benefits. The interaction with GenAI is so seamless and intuitive that the onboarding for new customers is frictionless, eliminating barriers to adoption and facilitating rapid technology spread. The high variability in potential inputs and priming of generative models allows for a diverse range of applications impacting nearly every imaginable aspect of people activities. This is a foundation of a new era of Artificial Intelligence.

In this primer we leveraged our knowledge of 50+ GenAI-related and VC-backed startups to reconstruct the technological stack of the forming GenAI space.

The technology & business stack of GenAI

Large tech companies are leveraging their existing technological and capital advantages to create the framework for the GenAI market landscape, which we are going to explore in this section.

While offering of the LLMs on the current scale and heavy focus on unstructured data are somewhat new, the other elements of the tech stack closely mirror those needed for any large computational modeling. Established companies in the field of traditional AI are at an advantage, as they can expand and repurpose preexisting software, infrastructure, and services. Download Complete Research

Business niches for GenAI startups

While large players are occupying a sizable portion of the GenAI tech stack, there remains more than enough room for GenAI startups to flourish. The landscape of AI and ML is continuously evolving, with new startups, technologies, and methodologies emerging regularly.

Bottom-right (AIOps): Here, startups may offer tools for easier adoption of LLMs, facilitating the initial process of customizing and implementing these models.

Ascending (Integration): Moving upwards represents the process of integrating LLMs into various applications and business operations. Startups could offer integration services, templates, or frameworks to streamline this, or build an entire end to end app for a selected market niche.

Moving left (Service platforms): As we move leftwards, the focus shifts from core LLM functionality to auxiliary services. This could range from platforms offering specialized training data, to marketplaces for LLM apps, to optimization tools. These firms may automate the need for certain experts.

This taxonomy can serve as a foundational overview for anyone looking to understand the current state of the LLM ecosystem. It’s also worth noting that the landscape of AI and ML is continuously evolving, with new startups, technologies, and methodologies emerging regularly. Let’s inspect each block in greater detail:

Future trends in GenAI

The future of the GenAI landscape is going to be defined by several processes:

1. Consolidation of major players
2. Rise in open-source adoption
3. Surge in service platforms
4. Expansion of skill marketplaces
5. Segment-specific applications
6. Regulatory oversight and standardization

Appendix 1: Reality & expectations of GenAI

While enhancing the users with great capabilities, the LLM-based service is neither a freebie, nor a cornucopia. Each implementation of LLMs carries its own advantages and downsides. In this section of the Appendix, we discuss what can and cannot be realistically expected from a GenAI model in each of the most popular use cases.

We start with primary properties of a pre-trained LLM model, underlying its strong sides and functionalities as well as build-in flaws. And we move to the current ways of augment LLM model to work around the flaws. Download Complete Research

Appendix 2: Startups across the GenAI tech stack

The table of 78 startups we have based our analysis on is presented in this section.
The states of startups are set to the August of 2023.

Credits
Author@lab45: Rinat Sergeev

This document navigates current airport challenges and presents advanced technology as the key to solutions. It offers profound insights into the future of global aviation, encompassing passenger management, sustainability, and technological integration.

What's inside

1. The not-so-smart airports of the present
2. The global travel shift: Current industry and market trends
3. The technological solutions making airports smarter
4. Solving for sustainability: A herculean task?
5. The global travel evolution: Upcoming industry and market trends
6. The global travel revolution: A futuristic rethinking, from first principles

The not-so-smart airports of the present

The not-so-smart airports of the present face numerous challenges. Operations suffer from capacity issues, flight delays, and inefficiencies. Passengers endure long queues, baggage mishaps, and limited amenities. Root causes include aging infrastructure, rising air travel demands, and heightened expectations. Solutions must address sustainability, accessibility, cargo flow, baggage handling, workforce shortages, and facility limitations.

The global travel shift: Current industry and market trends

The global travel shift: Current industry and market trends reveal airports' adoption of new technology and operational strategies to tackle challenges. Emerging trends include enhanced passenger experiences, optimized capacity, safety measures, regulatory compliance, cargo logistics, and sustainability efforts. These initiatives reflect a trifecta of technological innovation, evolving customer expectations, and sustainability goals. Download Complete Research

The technological solutions making airports smarter

Cutting-edge technology is revolutionizing airport operations, addressing core challenges. From AI-based gate allocation to IoT-enabled passenger flow monitoring, these innovations enhance efficiency, sustainability, and safety. Adoption levels vary, but promise a smarter future for airports.

Solving for sustainability: A herculean task?

The aviation sector faces sustainability challenges despite significant growth projections. Airports employ millions but also contribute to emissions, noise pollution, and land use issues. Innovative solutions are crucial to mitigate environmental impacts. New technologies offer hope, with initiatives focusing on energy efficiency, waste management, water conservation, carbon emissions reduction, sustainable construction, stakeholder engagement, and sustainable transportation. Adopting a "smart airport" mindset and leveraging advanced technologies are essential for sustainable development. Download Complete Research

The global travel evolution: Upcoming industry and market trends

Smart airport innovations offer incremental improvements, enhancing every aspect of the customer journey. From baggage tracking to disruption management, each innovation contributes to a vastly improved airport experience. These subtle enhancements, when integrated into a comprehensive system, create truly evolved airports. While current developments may seem marginal, they lay the groundwork for future radical transformations. Foundational changes in data and cloud technologies, along with private networks and digital twins, are revolutionizing airport operations. Innovations in transportation, such as urban air mobility and self-driving passenger vehicles, aim to streamline end-to-end customer transportation. With a growing focus on sustainability and continuous innovation, airports are poised for significant advancements in the coming years.

The global travel revolution: A futuristic rethinking, from first principles

Future airports represent the culmination of incremental improvements, resulting in a transformative rethinking of airport design, operation, and customer experience. Redefining each step of the passenger journey from first principles can revolutionize airport travel. From travel to the airport to reaching the final destination, autonomous vehicles offer seamless transportation, reducing stress and travel time. Check-in and security procedures can be streamlined through biometrics and digital identity, eliminating the need for documents and minimizing delays. Optimized luggage handling and security checks ensure efficiency and convenience. Boarding processes can be expedited through automated sorting and biometric verification, enhancing overall travel experience. Additionally, autonomous vehicles can facilitate efficient flight transfers, reducing stress for passengers during layovers. With innovative technologies and redesign of airport processes, future airports promise a more seamless and enjoyable travel experience for passengers worldwide. Download Complete Research

Credits
Lead Authors@lab45: Ankit Pandey