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BBVA takes an expert-led approach to AIYour employees are closest to your processes and problems and are often the best-placed to findAI-driven solutions. Getting AI into the hands of these experts can be far more powerful than tryingto build generic or horizontal solutions.BBVA, the global banking leader, has more than 125,000 employees, each with a unique set ofchallenges and opportunities. They decided to get AI into the hands of employees—working closelywith Legal, Compliance, and IT Security teams to ensure responsible use. They rolled out ChatGPTEnterprise globally, then let people discover their own use cases.“Normally, in a business like ours, building even a prototype requires technical resources and time,”says Elena Alfaro, Head of Global AI Adoption at BBVA. “With custom GPTs, anyone can createapps to solve unique problems—it’s very easy to start.”In five months, BBVA employees created over 2,900 custom GPTs—some of which reduceproject and process tim

<div class="bn-block-group" data-node-type="blockGroup"><div class="bn-block-outer" data-id="34fea767-40e2-4480-b6cb-cc033c2a8144" data-node-type="blockOuter"><div class="bn-block" data-id="34fea767-40e2-4480-b6cb-cc033c2a8144" data-node-type="blockContainer"><div class="bn-block-content" data-content-type="paragraph"><p class="bn-inline-content">BBVA takes an expert-led approach to AI</p></div></div></div><div class="bn-block-outer" data-id="6cac782c-33fd-4938-85b3-db4680d58b00" data-node-type="blockOuter"><div class="bn-block" data-id="6cac782c-33fd-4938-85b3-db4680d58b00" data-node-type="blockContainer"><div class="bn-block-content" data-content-type="paragraph"><p class="bn-inline-content">Your employees are closest to your processes and problems and are often the best-placed to find</p></div></div></div><div class="bn-block-outer" data-id="a20e71af-ad9f-4adc-8919-2c56d266cf83" data-node-type="blockOuter"><div class="bn-block" data-id="a20e71af-ad9f-4adc-8919-2c56d266cf83" data-node-type="blockContainer"><div class="bn-block-content" data-content-type="paragraph"><p class="bn-inline-content">AI-driven solutions. Getting AI into the hands of these experts can be far more powerful than trying</p></div></div></div><div class="bn-block-outer" data-id="c37b55f2-0075-42c9-9461-59dca339fe5b" data-node-type="blockOuter"><div class="bn-block" data-id="c37b55f2-0075-42c9-9461-59dca339fe5b" data-node-type="blockContainer"><div class="bn-block-content" data-content-type="paragraph"><p class="bn-inline-content">to build generic or horizontal solutions.</p></div></div></div><div class="bn-block-outer" data-id="262c81d5-a415-43bf-afc2-a8405b32306e" data-node-type="blockOuter"><div class="bn-block" data-id="262c81d5-a415-43bf-afc2-a8405b32306e" data-node-type="blockContainer"><div class="bn-block-content" data-content-type="paragraph"><p class="bn-inline-content"> </p></div></div></div><div class="bn-block-outer" data-id="b7871406-84a0-40f0-a7b4-f97c37c46e86" data-node-type="blockOuter"><div class="bn-block" data-id="b7871406-84a0-40f0-a7b4-f97c37c46e86" data-node-type="blockContainer"><div class="bn-block-content" data-content-type="paragraph"><p class="bn-inline-content"> BBVA, the global banking leader, has more than 125,000 employees, each with a unique set of</p></div></div></div><div class="bn-block-outer" data-id="f3cece36-ad22-434d-9967-2d376ca3407e" data-node-type="blockOuter"><div class="bn-block" data-id="f3cece36-ad22-434d-9967-2d376ca3407e" data-node-type="blockContainer"><div class="bn-block-content" data-content-type="paragraph"><p class="bn-inline-content">challenges and opportunities. They decided to get AI into the hands of employees—working closely</p></div></div></div><div class="bn-block-outer" data-id="65256ed8-2d6e-4c88-9dda-d05dc79b6ed8" data-node-type="blockOuter"><div class="bn-block" data-id="65256ed8-2d6e-4c88-9dda-d05dc79b6ed8" data-node-type="blockContainer"><div class="bn-block-content" data-content-type="paragraph"><p class="bn-inline-content">with Legal, Compliance, and IT Security teams to ensure responsible use. They rolled out ChatGPT</p></div></div></div><div class="bn-block-outer" data-id="1c912a19-6b4b-4850-9d44-5a54e1454f17" data-node-type="blockOuter"><div class="bn-block" data-id="1c912a19-6b4b-4850-9d44-5a54e1454f17" data-node-type="blockContainer"><div class="bn-block-content" data-content-type="paragraph"><p class="bn-inline-content">Enterprise globally, then let people discover their own use cases.</p></div></div></div><div class="bn-block-outer" data-id="cd7a0e26-fdd7-412a-b7ec-271e27986b4e" data-node-type="blockOuter"><div class="bn-block" data-id="cd7a0e26-fdd7-412a-b7ec-271e27986b4e" data-node-type="blockContainer"><div class="bn-block-content" data-content-type="paragraph"><p class="bn-inline-content">“Normally, in a business like ours, building even a prototype requires technical resources and time,”</p></div></div></div><div class="bn-block-outer" data-id="0a3cf930-d695-43e1-b1c4-8cf7c4d75011" data-node-type="blockOuter"><div class="bn-block" data-id="0a3cf930-d695-43e1-b1c4-8cf7c4d75011" data-node-type="blockContainer"><div class="bn-block-content" data-content-type="paragraph"><p class="bn-inline-content">says Elena Alfaro, Head of Global AI Adoption at BBVA. “With custom GPTs, anyone can create</p></div></div></div><div class="bn-block-outer" data-id="4c524c4b-1ea7-4784-9f50-cb7e58a4094d" data-node-type="blockOuter"><div class="bn-block" data-id="4c524c4b-1ea7-4784-9f50-cb7e58a4094d" data-node-type="blockContainer"><div class="bn-block-content" data-content-type="paragraph"><p class="bn-inline-content">apps to solve unique problems—it’s very easy to start.”</p></div></div></div><div class="bn-block-outer" data-id="ba51db56-a3d4-4ba6-aeed-236c43969e5c" data-node-type="blockOuter"><div class="bn-block" data-id="ba51db56-a3d4-4ba6-aeed-236c43969e5c" data-node-type="blockContainer"><div class="bn-block-content" data-content-type="paragraph"><p class="bn-inline-content">In five months, BBVA employees created over 2,900 custom GPTs—some of which reduce</p></div></div></div><div class="bn-block-outer" data-id="4f2a894e-0cc7-4c5d-bd66-45d80b17612c" data-node-type="blockOuter"><div class="bn-block" data-id="4f2a894e-0cc7-4c5d-bd66-45d80b17612c" data-node-type="blockContainer"><div class="bn-block-content" data-content-type="paragraph"><p class="bn-inline-content"> </p></div></div></div><div class="bn-block-outer" data-id="826eb39d-6f48-4c3d-ac73-93931d613e09" data-node-type="blockOuter"><div class="bn-block" data-id="826eb39d-6f48-4c3d-ac73-93931d613e09" data-node-type="blockContainer"><div class="bn-block-content" data-content-type="paragraph"><p class="bn-inline-content"> project and process tim</p></div></div></div><div class="bn-block-outer" data-id="13a4ff47-9c31-4598-9cee-b671f52d46cf" data-node-type="blockOuter"><div class="bn-block" data-id="13a4ff47-9c31-4598-9cee-b671f52d46cf" data-node-type="blockContainer"><div class="bn-block-content" data-content-type="paragraph"><p class="bn-inline-content"></p></div></div></div></div>

Goals:Optimize for the keyword: [main keyword]Include 3–5 related keywords: [list related terms]Make it engaging, easy to read, and factually accurate.Include a short, catchy title (under 60 characters).Write a compelling meta description (under 160 characters).Use clear H1, H2, H3 structure.Add a call to action (CTA) at the end.Ensure it’s written in [language/tone, e.g., English / formal / friendly / professional].Target audience: [describe audience].Output format:TitleMeta descriptionArticle body with SEO headingsList of target keywords at the end

ONE How to do the JSON promptTWO opdateTHREEEE

<div class="bn-block-group" data-node-type="blockGroup"><div class="bn-block-outer" data-id="16ace2eb-72d9-4453-ad83-f287c7b09449" data-node-type="blockOuter"><div class="bn-block" data-id="16ace2eb-72d9-4453-ad83-f287c7b09449" data-node-type="blockContainer"><div class="bn-block-content" data-content-type="paragraph"><p class="bn-inline-content">ONE How to do the JSON prompt</p></div></div></div><div class="bn-block-outer" data-id="021f3a65-e480-49a7-80f2-99c892080250" data-node-type="blockOuter"><div class="bn-block" data-id="021f3a65-e480-49a7-80f2-99c892080250" data-node-type="blockContainer"><div class="bn-block-content" data-content-type="paragraph"><p class="bn-inline-content">TWO opdate</p></div></div></div><div class="bn-block-outer" data-id="bfce9952-a81a-46df-a30d-3ad3570c1ef1" data-node-type="blockOuter"><div class="bn-block" data-id="bfce9952-a81a-46df-a30d-3ad3570c1ef1" data-node-type="blockContainer"><div class="bn-block-content" data-content-type="paragraph"><p class="bn-inline-content">THREEEE</p></div></div></div><div class="bn-block-outer" data-id="08f67a04-3a08-4092-9f3e-86ca365ea10d" data-node-type="blockOuter"><div class="bn-block" data-id="08f67a04-3a08-4092-9f3e-86ca365ea10d" data-node-type="blockContainer"><div class="bn-block-content" data-content-type="paragraph"><p class="bn-inline-content"></p></div></div></div></div>

EDIT1EDIT2EDIT3EDIT4EDIT5How Lowe’s improves product searchEnterprises seeing the most success from AI adoption are often the ones that invest time andresources in customizing and training their own AI models. OpenAI has invested heavily in our APIto make it easier to customize and fine-tune models—whether as a self-service approach or usingour tools and support.We worked closely with Lowe’s, the Fortune 50 home improvement company, to improve theaccuracy and relevance of their ecommerce search function. With thousands of suppliers, Lowe’soften has to work with incomplete or inconsistent product data.13AI in the EnterpriseThe key is in accurate product descriptions and tagging. But it also requires an understandingof how shoppers search, a dynamic that changes across product categories. That’s wherefine-tuning comes in.By fine-tuning OpenAI models, the Lowe’s team was able to improve product tagging accuracyby 20%—with error detection improving by 60%.Excitement in the team was palpable when we sawresults from fine-tuning GPT 3.5 on our product data.We knew we had a winner on our hands!Nishant GuptaSenior Director, Data, Analytics and ComputationalIntelligence

How Indeed humanizes job matchingWhen AI is used to automate and accelerate tedious, repetitive work, employees can focus onthe things only people can do. And because AI can process huge amounts of data from manysources, it can create customer experiences that feel more human because they’re more relevantand personalized.Indeed, the world’s No. 1 job site, uses GPT-4o mini to match job seekers to jobs in new ways.The power of whyMaking great job recommendations to job seekers is only the start of the Indeed experience.They also need to explain to the candidate why this specific job was recommended to them.Indeed uses the data analysis and natural language capabilities of GPT-4o mini to shape these‘why’ statements in their emails and messages to jobseekers. Using AI, the popular ‘Invite to Apply’feature also explains why a candidate’s background or previous work experience makes the joba good fit.The Indeed team tested the previous jobmatching engine against the GPT-poweredversion with the new, customized context.The performance uplift was significant:9A 20% increasein job applications startednotonly were more candidates likely to apply,but employers were more likely to hire them.A 13% uplift in downstream success—AI in the EnterpriseWith Indeed sending over 20 million messages a month to job seekers—and 350 million visitorscoming to the site every month—these increases scale up to significant business impact.But scaling up also meant using more tokens. To increase efficiency, OpenAI and Indeedworked together to fine-tune a smaller GPT model that was able to deliver similar resultswith 60% fewer tokens.Helping job seekers find the right jobs—and understanding why a given opportunity is right forthem—is a profoundly human outcome. Indeed's team has used AI to help connect more peopleto jobs, faster—a win for everyone.We see a lot of opportunity to continue to investin this new infrastructure in ways that will helpus grow revenue.Chris Hya

As a global leader in financial services, Morgan Stanley is a relationship business. Not surprisingly,there were some questions across the business about how AI could add value to the highlypersonal and sensitive nature of the work.The answer was to conduct intensive evals for every proposed application. An eval is simply arigorous, structured process for measuring how AI models actually perform against benchmarksin a given use case. It’s also a way to continuously improve the AI-enabled processes, with expertfeedback at every step.How it startedMorgan Stanley’s first eval focused on making their financial advisors more efficient and effective.The premise was simple: If advisors could access information faster and reduce the time spent onrepetitive tasks, they could offer more and better insights to clients.They started with three model evals:01Language translationMeasuring the accuracy and quality of translations producedby a model.02SummarizationEvaluating how a model condenses information, usingagreed-upon-metrics for accuracy, relevance, and coherence.03Human trainersComparing AI results to responses from expert advisors,grading for accuracy and relevance.These evals—and others—gave Morgan Stanley the confidence to start rolling the use casesinto production.