Artificial intelligence (AI) and the Cloud are two pinnacles driving innovative thinking and strategic implementations within today’s technology-led environment.
As highlighted in my recent article on AI activities in Insurance, $62bn has been invested in AI in 2020. Statista provides further insight on AI software revenue estimates in their In-depth: AI 2020 study with an expected revenue projection of $126bn by 2025.
Concurrently, the global Cloud computing market size is expected to grow from $371.4 billion in 2020 to $832.1 billion by 2025, at a CAGR of 17.5% — hybrid clouds standing as the most widely adopted Cloud type within large enterprises.
Analysts are now providing predictions combining both AI and Cloud technologies. The Cloud AI market was valued at $5.2 billion in 2020. By 2026, this is expected to more than double to reach $13.1 billion.
Over the past ten years, Cloud computing has moved from a concept into something that has wholly overrun our digital lives, whether personal or professional.
“As companies embraced the work from home model to safeguard employees’ well-being, Software-as-a-Service-based collaboration solutions and Video-on-Demand streaming and conferencing platforms have become highly popular and embedded within the way we do things.”
Still, AI and Cloud technologies are almost always discussed in isolation and are often not fully identified as integrally entwined. While we are still away from constructing a machine that is as clever and resourceful as a Westworld humanoid, we are taking the first steps to what is expected to be a highly inspiring journey.
Further, as more unique and complex business models emerge, both AI and the Cloud become enablers to deliver transparent and trusted sources of differential advantage. And the demand for these fully wedded bedfellows underpins growth in the direction generations want it to go. This is especially true for disruptive technologies in industries hindered by highly traditional models, such as insurance.
When we look at AI and Cloud technologies and combine them into a cohesive architectural design, we see pure alchemy happen: something more significant than the sum of the parts. And that does wonders for yielding sustainable sources of growth that align with today’s demand around ethics and values.
Why do AI and the Cloud go hand-in-hand?
At its simplest, the Cloud centralizes many data sources on multiple servers across the globe. That data is accessible from anywhere and at any time to achieve well-defined business outcomes. This structure is the antithesis of having everything stored on-site. You can do away with in-house servers and even the software required to manage the data.
For any business, large or small, the Cloud has clear benefits. As physical assets become digital, there is no need to maintain, update and manage locally based systems and software in highly obsolete, costly, and specialized ways. External “Cloud experts” are put in charge, thus effectively becoming the recipient of a very complex element of a business’s daily life as they accelerate the design and deployment of a new set of highly sophisticated capabilities. This engagement model enables enterprises to achieve significant savings and efficiencies as they grow and scale, while data needs to be accessed in real-time from anywhere around the world. It’s a way of boosting business effectiveness and easing innovative deployment in a very flexible, controllable, and affordable manner.
As shared by IBM, a well-deployed Cloud computing environment allows for “enterprise scalability.” combined with exceptional agility, security, and continuity.
“When fused with AI machines can respond, simulate and deploy consistent programs giving humans capacity for contemplation, judgment, and intention. Machines are then programmed to learn and apply that learning in a way that is not dissimilar to human intelligence. Of course, they can do it at lightning speed while utilizing far more data and far greater objectivity than a human being ever could.” IBM
“By combining Artificial Intelligence with Cloud computing, you get a vast network capable of storing unimaginable amounts of data but with a capacity to learn and improve on the go.”
What does AI in the Cloud look like?
Surprisingly, the Cloud and AI are only just really coming to life as best friends at a broader level. However, between them, their links are so substantial that they’ve given birth to a new concept, “AIaas, more fully known as AI-as-a-service.” The latter is the most straightforward service for those starting to use AI technologies without spending large amounts of money on updates to a company’s internal infrastructure, which is pivotal for startups and growth ventures. And from my recent reading, behavioral economic-orientated unicorn Lemonade was able to take great advantage of their understanding of both capabilities (and still is) to drive real-time micro-engagements and accelerate key moments of truth from pricing to claims.
Cloud-based AI means that the Cloud service integrates AI and machine learning into the specific software or application in use. In practice, this may include image recognition, facial recognition, geolocation services, virtual reality, or a particular algorithm for determining user risk profile. Integrating AI means that the average business can apply cognitive algorithms without incurring prohibitive costs and barriers.
As AI and the Cloud are integrated to achieve substantial results, we see companies pushing this further, investing and committing resources to such projects.
“The scale of the change and volumes of partnerships within the venture market means that Cloud technologies with AI capabilities will increase in scope. Its use will ultimately become de facto.”
The benefits are enormous and wide-reaching, especially when considering them to deliver on the requirements set within sustainable growth agendas.
AI in the Cloud in action
With 1,000s of growth ventures entering the digital space every day with various AI algorithms, the common element that connects them all is their use of unique proprietary algorithms to make sense of vast amounts of data. As these ventures collaborate with incumbent organizations, this adds another layer of complexity in the design of business architectures, including procedures to handle data privacy, compliance, and security. Growth ventures are adopting Cloud computing services due to their significant benefits, such as no initial infrastructure setup costs and the on-demand availability of computing services. They also collaborate with market leaders to reduce their overall business risk, particularly those regulated by the PRA or the FCA. This interest contributes to the growth of hybrid cloud services in enterprises that must enhance workload management and efficiently integrate DevOps teams. It also leads to identifying Cloud/ AI partners with a continuous pulse on the regulation by working closely with insurers across multiple markets.
Leading challengers within the finance sector, and insurance, in particular, cannot do without Cloud infrastructures. Two leading players able to provide near-to real-time servicing to their respective customer base include Stride and Lemonade (as highlighted above).
With funds of $1.7 billion, Stripe remains the largest AI-enabled FinTech delivering friction-free user-centric engagement within the finance sector. It provides a complete online B2B payment processing platform combined with powerful and easy-to-use APIs. Behind Stripe’s functionality, highly sophisticated machine learning is making progress to ensure speedy payment for its global user-base while identifying and fighting against invasive payment fraud detection without trustworthy users noticing.
With a market cap today of $8Bn+, Lemonade has changed the way millennials engage with renter insurance. In the US, Lemonade owns 30%-35% of the renter market, and this growing across a few key markets across Europe. The highly personalized business model is targeted at The HENRYs – High Earners, Not Rich Yet, and aims to promote unique customer experiences. AI facilitates a digital, hassle-free sign-up process and the settlement of claims in seconds (where needed) rather than days to build trust. It builds transparency within its user base through social good. All this acceleration, personalization, and usage-based engagement require a robust Cloud infrastructure.
In insurance, collaborations often stem from a need to access advanced algorithms such as intelligent messaging, profiling, and scoring mechanisms, easing targeted underwriting and pricing, predicting customer purchase patterns, gamifying engagement, adapting behaviors, accelerating claims payment, or helping identify fraud in real-time among others.
Many insurers are considering their re-platforming strategy to meet strategic objectives. I recently learned that AvivaSa embarked on an efficiency-focused digital transformation journey to enhance its customer sales experience by deploying paperless and digitized processes to remove complex unresponsive engagement activities moving its tech to the Cloud. Generali France also deployed a roadmap to embed cognitive intelligent services, combining two assistants Letizia and Leo, to facilitate voice-to-text for employees and help agents access crucial information to handle more effectively customer requests. These initiatives required the deployment of a variety of capabilities, including integration with IBM’s hybrid Cloud.
“Hybrid Cloud is about connecting the world, connecting data and information, and people, and processes together in a way that we can trust and rely on. That has such far-reaching effects for all of us.”
Bea Elbert Global Insurance, General Manager at IBM
The benefits of integrating AI and the Cloud
While there are benefits in deploying AI and Cloud together, such as cost savings, speed time to market, and scalability, a few fundamental issues cannot be underestimated, namely privacy and security, which are undoubtedly familiar monsters-under-the-bed for every technological and data development. Those with years of expertise thinking about the problem have shown great ability to build unique mitigation strategies to support their clients in many sectors. This is where good governance, compliance, structure, and an understanding of data laws must be in place.
Still, I will consider the benefits rather than the hindrance that AI and the Cloud can bring to our industry.
Combining AI & the Cloud helps develop businesses at a steady pace. Both require the deployment of sophisticated infrastructure and continuous advancements in technological development. Don’t bring AI in-house, as it will almost certainly ensure that your thinking is outdated before it sees the light. The latter is the reason why hybrid clouds are needed and force you to think bigger.
AI enables businesses to automate repetitive and labor-intensive tasks and ensure that humans focus their attention on those move-valued activities. A secured Cloud environment ensures the right balance and monitoring of AI-led tasks versus augmented human tasks. Where else to get those experiences tested but within a secured cloud environment.
Effectiveness results from well-deployed processes and workflows at speed across the value chain from product design, to risk assessment to claim settlement. The Cloud becomes the only financially viable option to eliminate unnecessary costs at scale, including onsite hardware and software costs.
▪ Customer engagement
Driving real-time customer experiences is at the core of a well-deployed AI + Cloud strategy. Both combined in unique ways facilitate responsive, personal, targeted, and engaging customer interactions. AI can identify patterns in customer interactions that yield the most effective and timely engagement approaches. Speed of insight comes from deploying the right cloud infrastructure.
▪ Data management
Data management is a vast and complex beast, particularly in legacy businesses with masses of historical data. The latter requires Cloud storage capabilities that place no limits on data volumes. Managing rafts of internal and external data is what the Cloud is meant to do. With AI’s ability to analyze insight and automate engagement, surprising results can certainly be achieved.
As insurance providers focus on the business of insurance, IT productivity is left to the expert. The latter means managing large-scale data clouds at speed to access the insight required to improve decision-making and overall productivity. Cloud technology helps on that path.
Reduced reliance on one single physical location means one is less at risk of significant disasters halting business operations in its tracks. Future disaster recovery is likely to be substantially faster, if not instantaneous. It is the reason why the Cloud and AI are such great friends.
Moving forwards with achieving sustainable growth
Combining AI and the Cloud will see massive growth over the next decade. However, which areas are ripe for the most sustainable development? As highlighted in the conclusions of last week’s article — the focus should be on the genuine sustainable and positive change for people and the planet in response to demands from new generations’ values and goals, who want a healthier and fairer planet, with a more beneficial and ethical lens on communities.
“At the moment, AI and the Cloud aren’t developing equally across all market segments within insurance. Some areas are seeing more significant investment and development than others. It seems evident that specific parts of the industry still have a way to go and will see exceptional growth opportunities if deployed with the customer, regulation, and ethics in mind. ”
AI and the Cloud must be seen as complementary capabilities if sustainable growth agendas are going to succeed. The pandemic has only accelerated awareness that these disruptive initiatives cannot be delayed any longer. As the disorder is left behind, it is the progress and renewed focus on a healthier, ethical and sustainable future that will remain, and that will happen through combining AI and the Cloud more effectively.
This article was first published on LinkedIn here
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