Eight AI experts share their advice on how to prepare for an AI-driven future.<\/p>\n","hero_image":{"ID":111894,"id":111894,"title":"Co-Pilots HERO","filename":"Co-Pilots-HERO.png","filesize":31466,"url":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Co-Pilots-HERO.png","link":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Co-Pilots-HERO.png","alt":"","author":"122","description":"","caption":"","name":"wp-attachment-co-pilots-hero","status":"inherit","uploaded_to":111890,"date":"2024-02-15 15:01:14","modified":"2024-02-15 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bg-dark","button_cta":"Download the Book","button_link":"#Autopilot-AI-Co-Pilots","page_content":false,"bottom_cta":{"cta_title":"Ready to Hit the Runway and Take Off Towards an AI Future?","body":"Now that you know what the future holds, it\u2019s time to start your journey with AI. Download our AI one-pager to help you get started on the right foot with AI.","button_link":"#Autopilot-AI-Co-Pilots","button_text":"Download the One-Pager","button_link_two":"","button_text_two":""},"social_share_text":"","cta_helper_text":"","secondary_color":"magenta","books_super_index":{"cover":{"ID":111893,"id":111893,"title":"Co-Pilots INDEX","filename":"Co-Pilots-INDEX.jpg","filesize":141054,"url":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Co-Pilots-INDEX.jpg","link":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Co-Pilots-INDEX.jpg","alt":"","author":"122","description":"","caption":"","name":"wp-attachment-co-pilots-index","status":"inherit","uploaded_to":111890,"date":"2024-02-15 15:01:02","modified":"2024-02-15 15:01:02","menu_order":0,"mime_type":"image\/jpeg","type":"image","subtype":"jpeg","icon":"https:\/\/www.drift.com\/wp-includes\/images\/media\/default.png","width":1200,"height":627,"sizes":{"thumbnail":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Co-Pilots-INDEX-150x150.jpg","thumbnail-width":150,"thumbnail-height":150,"medium":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Co-Pilots-INDEX.jpg","medium-width":1200,"medium-height":627,"medium_large":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Co-Pilots-INDEX.jpg","medium_large-width":768,"medium_large-height":401,"large":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Co-Pilots-INDEX.jpg","large-width":1200,"large-height":627,"1536x1536":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Co-Pilots-INDEX.jpg","1536x1536-width":1200,"1536x1536-height":627,"2048x2048":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Co-Pilots-INDEX.jpg","2048x2048-width":1200,"2048x2048-height":627,"third_width_square":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Co-Pilots-INDEX-324x324.jpg","third_width_square-width":324,"third_width_square-height":324,"profile_24":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Co-Pilots-INDEX-24x24.jpg","profile_24-width":24,"profile_24-height":24,"profile_48":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Co-Pilots-INDEX-48x48.jpg","profile_48-width":48,"profile_48-height":48,"profile_96":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Co-Pilots-INDEX-96x96.jpg","profile_96-width":96,"profile_96-height":96,"profile_150":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Co-Pilots-INDEX-150x150.jpg","profile_150-width":150,"profile_150-height":150,"profile_300":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Co-Pilots-INDEX-300x300.jpg","profile_300-width":300,"profile_300-height":300}},"description":"","footer":"Make AI the ultimate co-pilot for your business."},"chapters_content":[{"chapter_title":"","chapter_body":[{"acf_fc_layout":"body","body_text":"
When Orville Wright took to the skies in the world\u2019s first airplane, his hands never left the controls. Yaw, pitch, roll, and speed \u2014 every movement relied on his delicate manual input. It was taxing work: Every iota of the young aviator\u2019s brainpower was focused on keeping his flimsy wooden airplane safely in the air.<\/p>\n
Fast-forward a hundred years, and while today\u2019s pilots can <\/i>manually control airplanes, they don\u2019t most of the time. Automation systems, specifically autopilots, now handle more than 90% of flight time<\/span><\/a>, guiding the airplane through the climb, cruise, and descent.<\/p>\n But that\u2019s not to say pilots are without jobs \u2014 instead, they\u2019re free to focus on the bigger picture. Rather than fixating on every little movement, modern pilots devote their time and energy to thinking about all of the outside circumstances that impact the yaw, pitch, roll, and speed of the plane. They do things like communicate with air traffic control, monitor the weather, and check fuel, position, and time.<\/p>\n Autopilot radically transformed the aviation industry, empowering pilots to fly more smoothly, reliably, and accurately. Now, artificial intelligence (AI) is poised to do the same for people across all roles, functions, and sectors.<\/p>\n The launch of ChatGPT in late 2022 catalyzed both individuals’ and businesses\u2019 interest in AI. Since then, millions of people have poured countless hours into thinking about, experimenting with, and investing in it. And it\u2019s unlikely that this trend will change in the coming years: A recent IDC forecast<\/span><\/a> found that, by 2027, the global AI software market is expected to reach up to $251 billion \u2014 and, separately, the generative AI market is expected to grow to $55.7 billion.<\/p>\n With this burgeoning AI market comes the rare opportunity for businesses to transform the way they work \u2014 to save time with automation, simplify complex workflows, and drive better outcomes. And, given how many businesses are already investing in AI, now<\/i> is the time for go-to-market (GTM) leaders to carefully consider how AI can work for them so that they and their teams can stay relevant and thrive in the future.<\/p>\n That\u2019s why we called on eight of the brightest AI thought leaders we know \u2014 some of whom have been watching the AI industry for years<\/i> \u2014 to share their hottest takes, best tips, and recommended roadmaps to help you get on the runway with AI. By reading this book, you’ll learn about the history and predicted future of AI, its risks and benefits, and how to start leveraging AI today so you can become the pilot of your industry tomorrow.<\/p>\n So, please make sure your seat backs and tray tables are in their full upright position \u2014 because the AI revolution is about to take off \u2708\ufe0f<\/span><\/p>\n"}]},{"chapter_title":"","chapter_body":[{"acf_fc_layout":"body","body_text":" Everyone is a generative AI expert and every business is a generative AI leader \u2014 according to LinkedIn, anyways. But when you peel back the social media hype, the reality is more nuanced.<\/p>\n When assessed across the 10 dimensions of AI in Business\u2019s Score Card for Success<\/span><\/a> (such as culture, innovation, and talent) most organizations fall into the lowest two categories of AI adoption. This means that, in reality, the majority of companies are still novices in AI or just starting to explore what AI can do for them. Rarely are they exploiting the full benefits of AI at scale.<\/p>\n So, why is there a disconnect between hype and reality?<\/p>\n Here, it helps to consider the Gartner Hype Cycle \u2014 a graph used to assess the maturity, adoption, and implementation of new technologies. It charts the five hype phases that new innovations often go through, starting from a fresh idea to inflated expectations, and ultimately into productive use.<\/p>\n"},{"acf_fc_layout":"image","image":{"ID":111898,"id":111898,"title":"Chart","filename":"Chart.png","filesize":146434,"url":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Chart.png","link":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Chart.png","alt":"","author":"122","description":"","caption":"","name":"wp-attachment-chart","status":"inherit","uploaded_to":111890,"date":"2024-02-15 15:02:54","modified":"2024-02-15 15:02:54","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.drift.com\/wp-includes\/images\/media\/default.png","width":6365,"height":4285,"sizes":{"thumbnail":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Chart-150x150.png","thumbnail-width":150,"thumbnail-height":150,"medium":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Chart.png","medium-width":6365,"medium-height":4285,"medium_large":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Chart.png","medium_large-width":768,"medium_large-height":517,"large":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Chart.png","large-width":6365,"large-height":4285,"1536x1536":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Chart-1536x1034.png","1536x1536-width":1536,"1536x1536-height":1034,"2048x2048":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Chart-2048x1379.png","2048x2048-width":2048,"2048x2048-height":1379,"third_width_square":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Chart-324x324.png","third_width_square-width":324,"third_width_square-height":324,"profile_24":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Chart-24x24.png","profile_24-width":24,"profile_24-height":24,"profile_48":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Chart-48x48.png","profile_48-width":48,"profile_48-height":48,"profile_96":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Chart-96x96.png","profile_96-width":96,"profile_96-height":96,"profile_150":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Chart-150x150.png","profile_150-width":150,"profile_150-height":150,"profile_300":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Chart-300x300.png","profile_300-width":300,"profile_300-height":300}}},{"acf_fc_layout":"body","body_text":" When the Hype Cycle is applied to generative AI, it\u2019s clear where we actually stand. Ever since the launch of ChatGPT, most organizations have been in full experimentation mode, testing and trialing new tools while people’s expectations have steadily been mounting. You\u2019ve probably read the same headlines: Why 95% of Salespeople Will Be Replaced by AI Within 20 Years. Forget Freelancers \u2014 ChatGPT Can Write Your Content. AI Chatbots Run a Software Development Company.<\/p>\n The truth is, generative AI can\u2019t do all of that stuff \u2014 at least not yet.<\/p>\n When folks discover the limitations of AI, some will naively abandon their AI transformation programs. But for those who push through (hint: you should be one of them), the payoff will be immense. Because, even now, AI can<\/i> do a lot. It can wipe out tedious manual work, drive predictions from complex data, and make humans faster, smarter, and more efficient.<\/p>\n By sticking it out with AI, you\u2019ll be the first to drive gains from what it has to offer. As a result, when we do reach that plateau of productivity in the Hype Cycle, you\u2019ll already be leagues ahead of the competition.<\/p>\n"}]},{"chapter_title":"","chapter_body":[{"acf_fc_layout":"body","body_text":" ChatGPT can pass medical, law, and business school exams. It can understand and explain a funny joke, invent brand-new languages, and write tear-jerking Shakespearean sonnets.<\/p>\n The ChatGPT we know today is flexible, powerful, and impressive. But give it a year, and it\u2019ll likely feel as antiquated as a horse-drawn cart. If that seems unrealistic, just think back to GPT-1. In the span of a few years, OpenAI\u2019s GPT went from responding in repetitive and sometimes incoherent paragraphs to writing full-on poetry. Similarly, you can literally see the same rapid evolution in Midjourney\u2019s AI.<\/p>\n"},{"acf_fc_layout":"body","body_text":" These two examples point to the reality that AI is evolving at a breakneck pace. This is because tools like OpenAI\u2019s GPT and Midjourney were built with AI at their core, which means they can learn from their data, adapt to it, and improve all on their own. As a result, we\u2019re entering an exponential growth phase with AI.<\/p>\n The AI products we see today are simply the foundation of what is to come. And with improvements happening fast, it\u2019s important that your team is improving alongside AI \u2014 otherwise, you\u2019ll be stuck playing catch-up later on.<\/p>\n That\u2019s why you need to start planning and implementing your AI roadmap today. To do this, ask yourself: What problem is our team facing now that might be solved with AI? Where in our process can we use AI to drive more efficiency? And where will AI be able to generate the most value? Once you have identified which use cases and problem statements you want to address, create an AI roadmap that charts out how you will bring AI into your organization. Aim for a timeline of about three to six months.<\/p>\n By creating this roadmap, you will have a concrete guide to help you shift your company into gear with AI. Keep in mind that you don\u2019t have to overhaul everything about your business \u2014 even a little bit of AI can go a really long way in creating value.<\/p>\n The most important part of AI adoption is to simply get started. Since the businesses that move now <\/i>will be the ones to reap the biggest benefits, you don\u2019t want to wait for your industry to get smarter around you. So, get your roadmap in place and start driving progress with AI today.<\/p>\n"}]},{"chapter_title":"","chapter_body":[{"acf_fc_layout":"body","body_text":" Think about the tasks that dominate your days as a revenue professional \u2014 toiling over a messy first draft, picking out target accounts from an endless list, or piecing together personalized outreach from scratch.<\/p>\n Now, think about what your day would look like if you could free up 60-70%<\/span><\/a> of the time you spend on that work. Your schedule opens up. Your energy refreshes. Instead of drowning in monotonous work, you are free to focus on strategic initiatives like designing creative content or having conversations with prospects.<\/p>\n This is exactly what everyone was hyped about when generative AI first hit the mainstream. But what was truly revolutionary about the commercialization of it was that it turned the way we approach AI on its head \u2014 a UX revolution.<\/p>\n Whether it\u2019s Google\u2019s search algorithm or Netflix\u2019s recommendation system, AI has long felt like a magic trick that happens behind the scenes: Though we could never really tell what was happening, we trusted that we would get the outcome we wanted. However, when it comes to generative AI like ChatGPT, that\u2019s far from the case. Instead, generative AI puts you in the driver\u2019s seat where you can influence, manage, and even control it.<\/p>\n At its core, what this UX revolution means is that you can\u2019t treat generative AI like the AI that came before it. So, when it comes to how you engage with generative AI, the tools that you engage with, and how you use those capabilities on your team, you need to emphasize usefulness rather than just correctness. For that, you want to assess any generative AI you use on these three guiding principles:<\/p>\n With generative AI, there are benefits to be had for the entire revenue team. Whether that\u2019s crafting emails for high-intent prospects, instantly providing insights into a target account, or recommending solutions that will drive up sales effectiveness, generative AI tools have the potential to save time and drive efficiency.<\/p>\n But you will have nothing to gain unless you approach generative AI in the right<\/i> way. This means always focusing on ensuring the reliability, explainability, and steerability of any generative AI tool you use \u2014 because that is how you will truly be able to put your team in the driver\u2019s seat.<\/p>\n"}]},{"chapter_title":"","chapter_body":[{"acf_fc_layout":"body","body_text":" While we throw around the idea that we\u2019re currently living in an \u201cAI revolution,\u201d it\u2019s actually more accurate to say that we\u2019re experiencing three<\/i> concurrent AI revolutions.<\/p>\n If you\u2019ve so much as dabbled with any sort of GPT technology, then you\u2019ve already experienced the first revolution: AI that makes humans <\/b>more productive. Whether it\u2019s providing prompt suggestions to break your writer\u2019s block or translating chat conversations in real time, these AI agents help us humans work faster, smarter, and more efficiently.<\/p>\n The second revolution is a little more hidden: AI that makes machines <\/b>more productive. For example, manufacturers use digital twins \u2014 digital reconstructions of real-world equipment like jet engines \u2014 to monitor the health of their equipment. By modeling wear and tear using AI, manufacturers can pinpoint when equipment does (and doesn\u2019t<\/i>) need to be fixed, saving millions of dollars on unnecessary routine maintenance.<\/p>\n But it\u2019s the third revolution that people tend to overlook the most \u2014 and that is where AI makes AI <\/b>more <\/b>productive.<\/p>\n For the most part, AI tools operate in silos. An imaging system will buzz away in one corner, a chatbot in another, and a copy generator in a third \u2014 but these tools can\u2019t communicate with each other. While you can <\/i>manually piece together Frankenstein-like AI systems, the results are often inefficient, unproductive, and unreliable.<\/p>\n However, recently, it\u2019s become easier to build these coordinated AI systems. By using natural language processing (NLP) to get AI tools to talk to each other, you can now chain AI tasks together so that a human can give a command to one AI assistant and then communicate it to the other AI tools behind the scenes.<\/p>\n What might this look like in practice? Say you\u2019re a conversion specialist on a marketing team. You tell your AI agent, \u201cAngela matches our ideal customer profile (ICP) perfectly. Wherever she goes, I want you to personalize our offerings to her.\u201d From this command, the AI agent will coordinate with your generative AI tool to craft highly personalized copy, the social platform\u2019s AI to optimize ad targeting, and your on-site AI chatbot to personalize the ad landing page.<\/p>\n While this is only a vision of what\u2019s to come, this third AI revolution is not far off in the future. Soon, AI will be able to communicate with, collaborate with, and train each other, which means that humans will be able to execute strategies more easily and efficiently. When combined with AI for humans and AI for machines, these three AI revolutions will empower you to drive better results in every corner of your business.<\/p>\n"}]},{"chapter_title":"","chapter_body":[{"acf_fc_layout":"body","body_text":" The B2B world has already experienced dozens of disruptions: Cloud technology reimagined software delivery. Social media transformed how buyers interact with vendors. Mobile unchained buyers and sellers from their desks. And the internet\u2026well, the internet changed everything<\/i>.<\/p>\n With each of those disruptions, the most successful adopters followed the same continuous cycle: identify, experiment, implement, repeat. This adoption flywheel is what has empowered businesses to try out new technologies, find the right use cases, and scale on what works for them. And it\u2019s the same cycle that we need to follow now with AI.<\/p>\n Currently, companies are scattered across the AI maturity spectrum: Some are still learning about what the technology can do while others are steadily expanding their use cases. No matter where you currently are in your implementation of AI though, the four steps of the flywheel can act as a guide to ensure you have the right use cases in place.<\/p>\n Think about it as approaching AI adoption like a scientist. The first three steps of the flywheel encourage you to craft hypotheses, rigorously test them, and then make decisions based on those results. Here\u2019s a breakdown of each of these steps in the context of AI:<\/p>\n But remember, that\u2019s not where the flywheel ends.<\/p>\n With AI developing at a breakneck speed, it\u2019s only a matter of time before the AI tools you use now are superseded by new ones, your perfect use case is rendered imperfect, and your outstanding results are overshadowed by those of your competitors. Never assume that what worked yesterday will work tomorrow. That\u2019s why the last and most important step of the flywheel is to continue identifying, experimenting, and implementing AI because it\u2019s the repetition of going through this cycle that will truly make you able to succeed.<\/p>\n"}]},{"chapter_title":"","chapter_body":[{"acf_fc_layout":"body","body_text":" Seven out of every 10<\/a><\/span> change management initiatives fail. This is because organizations are naturally risk-averse and biased towards the status quo \u2014 and the bigger an organization is, the worse it gets. As a result, even the simplest of ideas can stall out.<\/p>\n When it comes to introducing an entirely new technology like AI \u2014 a tool that people are experimenting with at the individual level \u2014 that hesitance reaches an all-time high. That\u2019s why, to convince your company to implement AI, you need to drive strategic and cultural change. Here are three steps to do exactly that:<\/p>\n 1. Define Company-Wide Standards for AI Use<\/b><\/p>\n While individuals have the power to decide when and how they use a new AI tool, a company can\u2019t make those decisions on the fly. That\u2019s why you need to clearly outline standards that define how your company approaches AI. This means answering questions like: What security and privacy regulations do you want your AI tools to comply with? What is an acceptable (and unacceptable) AI use case? What measures will you put in place to ensure your output from the AI is up to quality?<\/p>\n Once you\u2019ve agreed on these standards, make sure that you put everything down on paper, so it can serve as a source of truth for your company. In addition, you might want to set up an internal AI council to ensure that each team\u2019s use of AI fits those standards, while also continuing to drive literacy on new AI. With these measures in place, you can set up guardrails that ensure your organization is leveraging AI responsibly.<\/p>\n 2. Redesign Your Team\u2019s Workflows<\/b><\/p>\n Although AI has already proven to save time for individuals everywhere, there\u2019s no guarantee that it leads to better outcomes. After all, if the time you saved is reallocated to answering Slacks or scrolling LinkedIn, you won\u2019t have made much of an impact on your bottom line.<\/p>\n That\u2019s why, as you transition to working with AI, you should redesign your team\u2019s workflows. For instance, if your team plans to use generative AI to create and repackage content, then you want to reallocate your team\u2019s efforts towards coming up with original ideas that the AI can accelerate on. By building a workflow that integrates AI, you can ensure your human team and AI are working together to drive greater results.<\/p>\n 3. Prioritize Quality Above All Else<\/b><\/p>\n Tools like generative AI have proven to boost a GTM team\u2019s speed and output. But with many generative AI tools relying on content in the public domain, these results often miss the mark on accuracy, relevance, and value.<\/p>\n So, as you explore and expand your company\u2019s AI use cases, prioritize the quality of your output. This might mean choosing a tool that is more grounded in your business context, using a content ingestion feature to educate the tool on your brand, or building processes that keep humans in the loop to ensure accuracy.<\/p>\n While experimentation land is a lot of fun, the ultimate goal with AI is to drive better results. The key to moving from individual to team acceleration isn\u2019t so much technical knowledge as it is strategic change, and by following these three steps, you can set that change in motion, and in no time, be paving your way to successful AI transformation.<\/p>\n"}]},{"chapter_title":"","chapter_body":[{"acf_fc_layout":"body","body_text":" Your Netflix home page looks nothing like your friend\u2019s \u2014 and that\u2019s only partly due to your superior taste.<\/p>\n For years, Netflix has used machine learning to identify the shows and movies you like, uncover patterns in your preferences, and then deliver perfect recommendation after perfect recommendation. As a result, B2C companies like Netflix have set a new bar for personalized experiences \u2014 even among B2B buyers. Today, 66% of B2B buyers<\/span><\/a> demand seamless and personalized experiences on the same level as those in the B2C space.<\/p>\n The problem is that personalizing for B2B buyers tends to be a taller order than for B2C buyers. This is because most B2B buyers are anonymous, with many often being reluctant to share their information. Their buying behavior is also more complex \u2014 what with the involvement of large buying committees and long approval processes. This makes it hard to understand what any given buyer is looking for, which in turn, makes personalization impossible.<\/p>\n And that was the case for a long time \u2014 until predictive AI hit the scene.<\/p>\n As companies like Netflix have proven, behavior doesn\u2019t lie. By finding patterns in your buyers\u2019 browsing behavior, you can gauge each individual buyer\u2019s intent, as well as their needs and interests. And it just so happens that AI is the ultimate pattern detector. A predictive AI tool can watch how a buyer interacts with your website \u2014 what pages they visit, what content they download, or what services they check out \u2014 to then predict their intent with impressive accuracy. And that\u2019s without knowing anything else.<\/p>\n With a predictive AI engine, you can just look at buyer behavior and personalize from there. For example, if someone\u2019s browsing behavior suggests that they\u2019re a high-intent marketing persona who is looking for a new marketing automation platform, you can roll out relevant case studies, send a custom message via a chatbot, or tweak the home page messaging to fit their interests. Suddenly, they\u2019re not looking at a generic website, but rather a highly personalized landing page.<\/p>\n In this way, predictive AI allows you to capture demand from anonymous buyers on your website, instantly segment website visitors based on their level of intent, and create targeted experiences for dream buyers. All the while, each new visitor that lands on your website helps to improve the AI\u2019s predictive model, boost its accuracy, and give you better results.<\/p>\n Ultimately, with predictive AI working behind the scenes, you can create a website experience that closes the gap in your conversion opportunities, brings together sales and marketing by ensuring you\u2019re handing over all the best leads, and deliver a smoother, more enjoyable buyer experience \u2014 one that will truly live up to your buyers\u2019 expectations.<\/p>\n"}]},{"chapter_title":"","chapter_body":[{"acf_fc_layout":"body","body_text":" Elite sportspeople win or lose by razor-thin margins. When Usain Bolt won his final 100m Olympic gold medal, he won by eight milliseconds \u2014 just 0.8% faster than second place.<\/p>\n B2B businesses are no different \u2014 they have competitors, and they\u2019re constantly racing to see who can come out on top. In congested industries, even the tiniest improvement in your product or GTM strategy can quickly snowball into market domination.<\/p>\n But the fact is that AI promises to improve your business by way <\/i>more than just a slim margin.<\/p>\nNow Is Your Opportunity to Embrace Generative AI | KATIE KING<\/a>, CEO, AI IN BUSINESS<\/a><\/h2>\n
Today\u2019s AI Is the Least Capable We\u2019ll Have (and It\u2019s Crazy Good) | PAUL ROETZER<\/a>, Founder & CEO, MARKETING AI INSTITUTE<\/a><\/h2>\n
Midjourney’s evolution from February 2022 to May 2023.<\/h6>\n"},{"acf_fc_layout":"image","image":{"ID":111897,"id":111897,"title":"Midjourney","filename":"Midjourney.png","filesize":762864,"url":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Midjourney.png","link":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Midjourney.png","alt":"","author":"122","description":"","caption":"","name":"wp-attachment-midjourney","status":"inherit","uploaded_to":111890,"date":"2024-02-15 15:02:00","modified":"2024-02-15 15:02:00","menu_order":0,"mime_type":"image\/png","type":"image","subtype":"png","icon":"https:\/\/www.drift.com\/wp-includes\/images\/media\/default.png","width":2660,"height":1960,"sizes":{"thumbnail":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Midjourney-150x150.png","thumbnail-width":150,"thumbnail-height":150,"medium":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Midjourney.png","medium-width":2660,"medium-height":1960,"medium_large":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Midjourney.png","medium_large-width":768,"medium_large-height":566,"large":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Midjourney.png","large-width":2660,"large-height":1960,"1536x1536":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Midjourney-1536x1132.png","1536x1536-width":1536,"1536x1536-height":1132,"2048x2048":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Midjourney-2048x1509.png","2048x2048-width":2048,"2048x2048-height":1509,"third_width_square":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Midjourney-324x324.png","third_width_square-width":324,"third_width_square-height":324,"profile_24":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Midjourney-24x24.png","profile_24-width":24,"profile_24-height":24,"profile_48":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Midjourney-48x48.png","profile_48-width":48,"profile_48-height":48,"profile_96":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Midjourney-96x96.png","profile_96-width":96,"profile_96-height":96,"profile_150":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Midjourney-150x150.png","profile_150-width":150,"profile_150-height":150,"profile_300":"https:\/\/www.drift.com\/wp-content\/uploads\/2024\/02\/Midjourney-300x300.png","profile_300-width":300,"profile_300-height":300}}},{"acf_fc_layout":"body","body_text":"
Generative AI Is a UX Revolution | JAM KHAN<\/a>, Former SVP of Product Marketing, 6SENSE<\/a><\/h2>\n
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AI Can Boost Efficiency in All Parts of Your Business | DR. AYESHA KHANNA<\/a>, Co-Founder & CEO, ADDO<\/a><\/h2>\n
Take a Flywheel Approach to AI Adoption | MATT TIPPETS<\/a>, SVP of Product, Drift<\/a><\/h2>\n
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The 3 Ways to Break Out of AI Experimentation Land | MEGHAN KEANEY ANDERSON<\/a>, Head of Marketing, JASPER<\/a><\/h2>\n
Predictive AI Is the Key to Unlocking Personalized Experiences | DON SIMPSON<\/a>, CEO, LIFT AI<\/a><\/h2>\n
Future AI Will Reinvent Every Team, Function, and Industry | DANILO MCGARRY<\/a>, Top 20 in the World for AI<\/h2>\n