Nov 15, 2023
Case Studies: How do businesses use AI?
Sales and marketing: Coca-cola, Cosabella, Sephora
Operations: JP Morgan, KLM Royal Dutch Airlines
Chain management: UPS
Healthcare: IBM Watson Health
Energy management: Enel
Agriculture: Blue River Technology
Legal services: eBrevia
Insurance: Lemonade AI
Education: Carnegie Learning
Sports: Second Spectrum
Real estate: Compass
Hospitality: Hilton hotels
Government: United States Internal Revenue Service (IRS).
Environmental management: Microsoft
Social media: Hootsuite
Humanitarian aid: United Nations World Food Programme (WFP)
Art: Next Rembrandt
1. Sales and marketing: Coca-cola, Cosabella, Sephora
Coca-cola incorporated an AI-driven marketing system named Albert to enhance its online advertising strategies.
Albert employs machine learning schemes to scrutinize customer information, uncovering trends and valuable insights that can be harnessed to fine-tune digital ad campaigns.
This system has the capacity to modify advertising strategies in real-time, taking into account variables like consumer behavior, inclinations, and past purchases.
After adopting Albert, Coca-Cola witnessed considerable enhancements in its online advertising initiatives. The system aided the corporation to increase its return on investment (ROI) by refining advertising expenditure and zeroing in on the most lucrative customer segments.
Also the Italian high-end lingerie retailer, Cosabella, opted to transition its online marketing to Albert. This decision was part of their 3-year business revamping plan.
Albert's role was to independently execute and supervise digital advertisements and marketing activities, such as honing in on a high-value audience and boosting paid-search ROI.
After partnering with Albert for a month, Cosabella witnessed a 50% increase in social and search return on ad spend (ROAS) while decreasing its ad spend by 12%. By the end of the third month, Cosabella reported a remarkable 336% ROAS alongside a substantial 155% increment in revenue (Q4, 2016).
Consequently, in 2016, Cosabella resolved to abandon traditional advertising and marketing agencies for its online marketing operations.
Sephora uses an AI-driven framework coined Virtual Artist, crafted to bolster the user experience and fuel revenue growth. This platform leverages augmented reality alongside machine learning algorithms to facilitate customers in virtually testing a variety of makeup products.
Customers can utilize the Sephora application to capture their face image and subsequently apply diverse makeup items to envision their real-life appearance.
The platform employs machine learning to propose personalized product suggestions, taking into account the customer's skin colour and preferences.
Post the integration of the Virtual Artist platform, Sephora has documented remarkable strides in customer interaction and sales performance.
The platform has been instrumental in augmenting customer contentment and curtailing product returns, courtesy of the newly introduced facility allowing customers to experiment with makeup virtually prior to actual purchasing.
Interestingly, Sephora recorded an 11% surge in sales following the integration of an AI-fueled recommendation engine within its app.
2. Operations: JP Morgan, KLM Royal Dutch Airlines
JP Morgan, America's most massive bank, once dedicated numerous hours utilizing legal experts and loan officers to analyze financial transactions.
However, it has now employed an AI-powered system known as COIN (Contract Intelligence) to tackle the arduous task of deciphering commercial-loan agreements, thereby conserving almost 360,000 hours on an annual basis.
The establishment pronounces that this platform has considerably diminished the duration needed for document reviews and loan-servicing errors, which were previously the result of human misinterpretations in processing 12,000 new contracts annually.
COiN leverages machine learning paradigms to sift through an enormous amount of data extracted from a range of sources, such as bills, receipts, and diverse financial paperwork. With the incorporation of COiN, JPMorgan Chase has registered notable enhancements in its internal operations.
KLM, a notable name in the airline industry, has effectively utilized an "AI-facilitated human agent" framework to bolster their prevailing customer support unit.
As soon as an agent receives an incoming inquiry via social media platforms, the AI presents a suggested reply, based on training from 60,000 KLM-related questions and responses.
The agent then assesses the correctness of the provided answer and revises it if necessary before dispatching it through the relevant social media platform.
The platform can differentiate between various social media outlets - crafting lengthy replies for email queries and using under 140 characters for Twitter responses.
Cumulatively, it has led to a 35% efficiency surge, with nearly a third of customer inquiries being resolved by this method. This has facilitated agents to dedicate more time to genuine customer interactions and better comprehend their actual needs.
3. Chain management
UPS, has adopted an AI-driven route enhancement system called ORION (On-Road Integrated Optimization and Navigation).
This system aims to streamline their delivery paths efficiently.
ORION employs machine learning techniques to analyze extensive data, comprising traffic flux, road obstructions, and meteorological elements, to establish the most effective delivery routes for UPS personnel.
The program can modify routes instantaneously based on evolving circumstances like traffic hold-ups or road blockages. From the moment UPS began employing ORION, they have observed substantial amplification in productivity and cost-effectiveness.
The platform has significantly assisted in refining their delivery paths, decreasing the distance covered and enhancing overall delivery durations.
Moreover, by leveraging AI for route optimization, UPS has managed to trim down their annual delivery distances by a staggering 8.4 million miles - a testament to the convenience of using everyday language in describing complex AI systems.
By exploiting Natural Language Processing (NLP) and machine learning models, Watson for Oncology analyses extensive patient information encompassing medical backgrounds, laboratory findings, and other diagnostic examinations.
The software tailors treatment suggestions for each patient according to their unique health requirements.
Once Watson for Oncology was integrated, healthcare providers noticed a considerable elevation in the precision and efficiency of cancer detection and management.
This technology has enabled physicians to pinpoint alternative treatment modalities that were previously missed and circumvent potential healthcare mistakes.
Siemens has launched an AI-infused platform known as Siemens Digital Enterprise Suite, a tool aimed at enhancing their manufacturing procedures.
This setup employs machine learning formulas to analyze substantial volumes of data deriving from various entities like sensors, machinery, and other production equipment.
This suite provides real-time knowledge about manufacturing processes while spotting areas that could benefit from optimization and enhancement.
With the adoption of the Siemens Digital Enterprise Suite, noticeable advancements in efficacy and productivity have been reported by the company.
The platform has aided Siemens in fine-tuning their manufacturing protocols, diminishing idle periods, and elevating the overall functionality of equipment.
6. Human Resources
Unilever offers an exemplary instance of AI application in human resources, where they installed an AI-driven hiring platform known as HireVue.
This system is designed to simplify the recruitment process and enhance candidate selection.
HireVue employs machine learning algorithms to decipher video interviews conducted by prospective employees. It can recognize patterns in applicant behaviour, such as non-verbal cues and facial reactions, to yield insights about their appropriateness for a certain position.
Since the incorporation of HireVue, Unilever has witnessed considerable enhancements in the productivity and accuracy of its recruitment procedure.
The system has enabled the company to pinpoint high-calibre candidates more promptly and precisely, thus curtailing both the duration and expenditure linked to the recruitment process.
Darktrace has engineered an AI-driven cybersecurity platform known as the Enterprise Immune System.
Its purpose is to assist businesses in promptly detecting and reacting to cyber threats. The platform utilizes machine learning algorithms to analyze a vast amount of data from various data points such as network traffic, user actions, and other system records.
It has the ability to discern unusual activities and pinpoint potential threats before they inflict harm on the organization.
Since adopting the Enterprise Immune System, Darktrace's clients have seen notable enhancements in their capacity to detect and counteract cyber threats.
The platform has aided companies in uncovering hitherto unknown threats and implementing remedial measures to curb further harm.
8. Energy management
Enel has incorporated an AI-driven energy management system named Enel X, to streamline its energy consumption and distribution process.
Enel X leverages machine learning algorithms to examine copious amounts of data from diverse sources encompassing energy utilization and generation data, climatic conditions, and key data from the energy market.
This technology is capable of providing immediate insights into patterns of energy demand and usage, which aids Enel in fine-tuning its energy consumption and distribution in harmony with fluctuating scenarios.
Since integrating Enel X, the firm has witnessed remarkable enhancement in cost savings and energy efficiency. The system has supported Enel in refining its energy consumption and distribution strategy, diminishing wastage and enhancing overall efficiency.
Blue River Technology offers an illustrative example of AI's role in modern farming. They have engineered an AI-driven crop management system known as See & Spray. This innovative tool aids farmers in maximizing their crop production while cutting down on herbicide usage.
A combination of computer vision and machine learning empowers See & Spray to discriminate between crops and weeds within a farmland. By specifically targeting the unwanted plants with herbicides, it not only lowers the volume of herbicides required but also mitigates their interference with crop growth.
Farmers employing See & Spray have observed a noteworthy enhancement in crop yield and a considerable reduction in herbicide use, supporting optimized farm management, cost-effectiveness, and a sustainable farming approach.
10. Legal services
eBrevia has engineered an AI-fueled contract examination platform, intended to aid law practices and corporate law units in automating the process of contract scrutiny.
The platform leverages natural language processing (NLP) and machine learning algorithms to investigate and draw out critical elements from contracts such as indemnification clauses, termination stipulations, and change of control clauses. The system can pinpoint potential hurdles or contradictions within the contract and offer strategies for rectifying these issues.
Upon integrating eBrevia, both law enterprises and corporate legal divisions have observed substantial advancements in efficiency and cost-effectiveness. It has enabled them to mechanize the contract review process, thereby minimizing the time and resources necessary for contract analysis and review.
Lemonade AI has brought into play an AI-fuelled platform for handling claims, aiming to magnify the pace and precision of claim settlement.
The platform employs natural language processing (NLP) coupled with machine learning mechanisms to analyze claims and evaluate fraud risk.
The system has been designed with capabilities to autonomously approve certain claims, thereby minimizing the necessity for human meddling, and it also flags potential fraudulent instances for deeper inquiry.
Post the integration of this AI-driven claims management platform, Lemonade has witnessed substantial enhancements in claim resolution speed and fiscal savings. This platform has enabled the firm to automate claim procedures, thereby shrinking the duration and resources needed for managing claims.
Carnegie Learning has brought forth an AI-powered mathematics tutoring platform named Mika.
The purpose of Mika is to tailor learning experiences to individual students. Mika's core functions revolve around machine learning algorithms that track and understand each student's unique learning trajectory.
It then provides customized feedback and guidance based on these insights. This way, the platform caters to specific needs, offering personalized suggestions for further study and drills. The introduction of Mika has had substantial positive impacts on both educators and learners who have employed the system.
They have noticed marked advancements in student participation and achievement levels. Not only has the platform enhanced mathematical acuity among students, but it has also boosted their self-belief by offering bespoke learning journeys catering to their distinct needs.
Netflix has adopted an AI-propelled recommendation system, aimed at offering bespoke content suggestions to its users.
It employs machine learning procedures to analyze users' watch histories and preferences, subsequently providing customized content recommendations.
The system excels at recognizing patterns within user behavior, making personalized suggestions based on their distinct interests. Since the advent of this recommendation system, Netflix has noticed a substantial enhancement in user engagement and retention rates.
This system has bolstered user satisfaction by delivering individually curated content recommendations, aligning with their unique tastes. Netflix's usage of AI for content suggestions prompts 75% of viewing, thus retaining subscribers through hyper-personalization.
Second Spectrum has engineered an AI-enabled platform aimed at offering instantaneous insights and analyses for basketball matches.
Utilising machine learning techniques, the platform scrutinises player movements and interactions, thereby giving real-time feedback and suggestions to coaches and players. It can discern patterns and tendencies in player actions, and propose adjustments to gameplay strategies.
After deploying the AI-backed platform, Second Spectrum has succeeded in delivering invaluable insights and feedback to coaches and players which aids in enhancing their court performance. The system facilitates teams in pinpointing areas needing improvement and making tactical modifications promptly.
15. Real estate
Compass has integrated an AI-driven platform constructed to offer customised property suggestions for both buyers and sellers.
The platform employs machine learning algorithms to analyze real estate listings and deliver customised property options that resonate with a buyer's predilections. The system can discern patterns in the buying activities of customers and supply recommendations anchored on their likes and choices.
Post the integration of the AI-driven platform, Compass has reported substantial enhancements in customer interaction and contentment.
The system has been instrumental in refining the experiences of buyers by offering them personalised suggestions attuned to their unique requirements.
Hilton hotels chain has integrated an AI-run concierge service, named Connie, that gives individualized suggestions and support to the guests.
Relying on machine learning algorithms, Connie dissects guests' inclinations to offer customized reviews on local eateries, attractions, and happenings.
The system can interpret everyday language inquiries and furnish reliable answers immediately. By supplying personalized help and advice, this system has enhanced guests' experiences, making their visits more satisfying and unforgettable.
With the introduction of Connie, Hilton has noticed considerable enhancements in client contentment and interaction.
17.AI for retail
Amazon has introduced an AI-driven suggestion system, purposed to offer bespoke product suggestions to its customers.
The said system leverages machine learning algorithms to dissect customers' browsing and purchasing habits, subsequently supplying individualised products proposals aligned with their likes and preferences.
The system is proficient in discerning patterns within customer behaviour, thus formulating recommendations based on their unique requirements. The system has assisted in elevating customer shopping experiences by delivering them personalised product suggestions pertinent to their necessities and interests.
Post the introduction of the AI-based suggestion system, Amazon has noticed considerable enhancements in customer interaction and sales.
18. AI for government
United States Internal Revenue Service (IRS) has integrated an AI-enhanced platform aimed at detecting and nullifying tax fraud.
Utilizing machine learning principles, the platform examines tax files to pinpoint potential instances of fraud. It identifies patterns within these tax returns and suggests areas for further scrutiny.
With the incorporation of this AI-enabled platform, the IRS has witnessed a remarkable boost in its capability to identify and impede tax fraud.
This system has facilitated the detection of fraudulent cases that might have slipped past conventional methods, ultimately decreasing the number of fraudulent refunds distributed annually.
19. Environmental management
Microsoft has established an AI-driven platform committed to enhancing energy use efficiency in its data centres.
This platform employs machine learning algorithms to examine data derived from sensors among other sources, generating immediate suggestions for optimizing energy utilization. It can discern patterns in energy consumption and advise on strategies to curb waste and augment efficiency.
Following the introduction of this AI-enabled platform, Microsoft has noted remarkable cuts in energy use and carbon emissions.
This system has facilitated the firm's attainment of its sustainability targets by diminishing its ecological footprint and advocating for resource efficiency.
Airbus has utilized an AI-fueled predictive upkeep framework that's designed to foresee potential malfunctions with aircraft components before they escalate into bigger issues.
The framework employs machine learning algorithms to analyze data from different sources, including sensors, and provides predictions about the servicing or replacement timeline for various components.
It's capable of discerning patterns in component operations and offers maintenance suggestions based on this information.
Since the deployment of this AI-empowered predictive upkeep framework, Airbus has witnessed a substantial enhancement in aircraft dependability and safety. It has aided the firm in curtailing the incidence of unplanned maintenance activities and minimizing aircraft downtime.
Komatsu has incorporated a platform powered by AI, intended to enhance the functioning of its construction machinery.
This system employs machine learning algorithms for scrutinizing data derived from sensors and other channels, advancing real-time proposals for maximizing equipment utilization.
The platform can discern patterns in equipment operations and offer suggestions for diminishing wastage while augmenting efficiency.
Following the integration of this AI-enabled platform, Komatsu has observed notable enhancements in machinery performance and effectiveness.
The platform has steered the firm towards cutting back on fuel usage, reducing idle time, and bolstering overall productivity.
NVIDIA focuses primarily on creating graphics processing units (GPUs) for various uses, including gaming. They've launched an AI-driven platform known as NVIDIA DLSS (Deep Learning Super Sampling) which aims to augment both the functioning and visual appeal of games.
This platform harnesses the power of deep learning algorithms to analyze graphic data, thereby producing high-definition images instantly.
It's capable of discerning patterns within graphic data, subsequently making informed predictions on optimizing image clarity and performance.
Post integration of the NVIDIA DLSS platform, game creators have experienced considerable enhancements in gaming performance and visual excellence. The platform has effectively minimized GPU exertion, resulting in elevated frame rates and a seamless gaming experience, using everyday human language.
23. Social media
Hootsuite has integrated an AI-driven attribute known as "AdEspresso by Hootsuite". This feature is engineered to assist enterprises in enhancing their advertisement campaigns on social media.
Employing machine learning algorithms, it scrutinizes data extracted from a plethora of sources, including the performance of ads on social media and patterns in audience behavior. It is adept at detecting behavioral patterns among audiences and providing suggestions for boosting ad expenditure efficiency, precision in ad targeting, and communication tactics.
Post the implementation of AdEspresso by Hootsuite, companies have reported substantial enhancements in their advertising efficacy on social media. The platform has facilitated businesses in augmenting their ad expenditure yield, refining the accuracy of targeting, and diminishing the time implication for launching campaigns.
24. Humanitarian aid
United Nations World Food Programme (WFP) stands as a beacon showing how AI can be harnessed for humanitarian purposes.
It has embraced the power of AI through the advent of the "Building Blocks" platform, which is engineered to enhance the proficiency and efficacy of its aid distribution methods.
The platform employs machine learning algorithms, analyzing a plethora of data including satellite imagery, climatic trends, and social media chatter.
This enables it to pinpoint needy locations, foresee potential crises, and fine-tune aid delivery routes.
Having adopted Building Blocks, WFP has noted substantial enhancements in its aid delivery methods. This platform has empowered the organization in accelerating and refining aid delivery, curtailing wastage and ineffectiveness, and extending their reach to a larger number of distressed individuals.
Tesla has integrated a system powered by artificial intelligence named "Autopilot" aimed at increasing both the safety standards and efficiency of its automobile offerings.
This sophisticated platform utilizes machine learning algorithms to process data collected from a variety of sensors such as cameras and radar systems, allowing it to identify potential hazards and other automobiles on the roadways.
Through instantaneous decision-making regarding braking, steering, and accelerating, it effectively minimizes collision risk and enhances overall driving execution.
Since initiating the Autopilot system, Tesla claims to have witnessed substantial enhancements in vehicle safety and operation. This platform has assisted the firm in curbing accident occurrences while boosting its vehicles' efficiency.
Next Rembrandt is a joint venture, orchestrated by ING Bank in conjunction with J. Walter Thompson Amsterdam, aimed to power of machine learning algorithms to conjure up a fresh "Rembrandt" masterpiece, mimicking the legendary artist's distinctive aesthetic touch.
The project embarked on its journey by meticulously scrutinizing the array of elements in Rembrandt’s paintings, which encompassed everything from brushwork patterns and compositional structure to color schemes. Utilizing these insights, the machine learning algorithms crafted a novel painting emulating Rembrandt's unique style, realized through a 3D printer.
The end product? An exquisite piece of art marked by elaborate brushstrokes and meticulous details, bearing an uncanny resemblance to a genuine Rembrandt creation.
Even though this artwork wasn't crafted by the maestro himself, it showcased how AI can be utilized to generate art resonating with the flair of iconic artists.
Such instances merely scratch the surface when it comes to the plethora of potential applications for AI across diverse business sectors. As advancements in AI technology persist, we can expect a continuous emergence of novel applications, paving new avenues for businesses to augment their operational efficiency and foster innovation.
The Netx Rembrandt
Nowdays, the successful integration of artificial intelligence has a lot of evidences.
A comprehensive methodology encompassing strategic planning, technological solutions, human resources, data management, and adherence to ethical AI guidelines is essential.
While the algorithms are simply the surface layer, they have the potential to facilitate a complete transformational shift in an organization when supported by the requisite foundational components.
As generative AI progresses, adopting this thorough strategy will become increasingly crucial for businesses aspiring to attain a dominant position in an AI-driven market landscape.
Don't forget that leveraging AI-powered tools like Editby, companies can create personalized content that:
aligns with individual intentions;
improving the overall customer experience; and
increasing conversion rates.
Learn more here: Editby