Our world is moving toward accelerated computing, with workloads being adapted into efficient AI workflows—including our Monks.Flow professional managed service, which connects exceptional talent with the greatest AI tools, APIs and models, all within easily orchestrated pipelines. Integrated with the latest innovations from NVIDIA, AWS and other technologies, we’ve built best-in-class solutions across each of our practices: Content, Data and Media. At GTC, we’ll demonstrate these solutions, and attendees can get a chance to see them in action.

Check us out at the NVIDIA XR Zone Pavilion – Monks.Flow and OpenUSD.

Stop by the NVIDIA XR Zone Pavilion to get a sneak peek at Monks.Flow, an AI-centric professional managed service that streamlines how humans and machines interoperate at every step of the marketing journey, from building business intelligence to delivering hyper-personalized creative content. Monks.Flow leverages NVIDIA CloudXR and the NVIDIA Omniverse OpenUSD development platform to help brands virtually explore different customizable product designs and unlock scale and hyper-personalization across any customer journey.

Stop by the AWS booth (#708) for more on Monks.Flow, implementations and its use cases.

In addition to the NVIDIA XR Zone Pavilion, you’ll also find our featured space at the AWS booth, #708. There, we’ll have a dedicated kiosk where you can meet the Monks and learn all about the AI solutions built on AWS and NVIDIA technology that we’re delivering to CMOs.

We have designed a state-of-the-art workflow that helps marketers make better decisions by allowing them to chat directly with their customer personas, which are enriched with a comprehensive knowledge base and multiple large language models. This workflow delivers a tailored, secure, and scalable AI language framework for clients. Providing an understanding of language, context, emotion, and tone, these demos showcase the types of dynamic, low-latency interactions made possible by AI.

Wormhole, our out-of-this-world animatronic alien, will be stationed at our kiosk, ready to chat with passersby. Connected to the cloud and powered by AWS AI tools, including Bedrock, Amazon Sagemaker and Amazon Polly, Wormhole demonstrates lifelike movement and speech and serves as a prototype for the kinds of human-to-robot creations that are made possible by advances in AI—with a touch of humor.

After chatting up Wormhole, stick around for a showcase of Novo, a lifelike virtual human. The ultra-realistic avatar integrates NVIDIA NeMo and NVIDIA Audio2Face, both part of the NVIDIA ACE suite of technologies, to deliver an immersive and engaging conversational experience.

Don’t miss informative talks throughout GTC.

How Media.Monks Builds Generative AI Experiences (March 20, 10am PDT)

If you want to learn more about Wormhole and how it all came together, don’t miss this talk led by Iran Reyes (VP, Global Head of Engineering, Media.Monks), Peter Altamirano (VP, Global Head of Technology, Media.Monks), and Gregoire Rouyer (Global Partner Strategy Lead, AWS). Taking viewers behind the scenes into the creation of Wormhole, the trio will discuss relevant AWS AI tools, including Bedrock, Amazon Sagemaker and Amazon Polly. Learn how it was built and pose your questions to the team!

Revolutionizing Fan Engagement: Unleashing the Power of AI in Software-Defined Production (March 21, 10am PDT)

Presented by Lewis Smithingham, SVP of Innovation and Creative Solution at Media.Monks, this talk will discuss how software-defined broadcast and Monks.Flow for Media and Entertainment are transforming broadcast and unlocking cost reduction, content scalability, talent acquisition, sustainability and more.

Our advanced live production pipeline is powered by NVIDIA hardware, including NVIDIA RTX 6000 Ada Generation GPUs and NVIDIA L40S GPUs, to support 8K 60fps pipelines for live broadcast. Media.Monks’ latest iteration of broadcast and content delivery tools integrates NVIDIA Holoscan for Media to serve hyper-personalized content to fans across new media formats. In order to build this content at speed and scale, Media.Monks utilizes the NVIDIA DeepStream SDK, part of the NVIDIA Metropolis platform for developing vision AI solutions, to identify in-frame images within specific broadcast segments. It also uses the NVIDIA NeVA model, hosted with the NVIDIA Triton Inference Server, which etches relevant metadata information to accurately deliver the segment to interest-based audience groups. Retrieval augmented generation (RAG) is used to aggregate and segment audience data sets, and, in turn, serve hyper-personalized content to viewers with incredible precision. Finally, the software-defined production pipeline brings together a series of technologies from AWS, including EC2 (instance types G4dn and G5), CloudFront, Route 53, CloudWatch, and CloudTrail.

Watch the presentation to learn how it all comes together to help brands and broadcast rights-holders reach incredibly specific and granular audiences—for example, a basketball viewer in Utah who likes rap music, collecting sneakers, and gaming.

AI Orchestration for the CMO with Monks.Flow

Take a look at Monks.Flow, our professional managed service for marketers that trades manual workloads for AI workflows. The platform-agnostic orchestration tool is designed to work across an organization’s existing tech stack and is built around the unique needs of the enterprise. Monks.Flow and our consulting practice help CMOs reduce costs, select tools and partners, develop model and owned data strategies, integrate teams, build business intelligence and maximize marketing impact.

Our latest Monks.Flow release is Persona.Flow, which provides deep consumer intelligence by simulating detailed, interactive consumer personas that are engaged in a question-and-answer format. Facilitated by a RAG framework that orchestrates brand and factual consumer data, Persona.Flow provides brands with the insights they need to fuel content generation and creativity at scale.

While we’ll have videos at the kiosk inside AWS booth #708 demonstrating the abilities of Monks.Flow, VP, Emerging Tech and R&D Sander van der Vegte and EVP, Innovation Michael Dobell will also be presenting on the solution at the nearby AWS In-Booth Theatre, located at the AWS booth. Stop by on March 20 at 1:50pm PDT for the formal presentation, or stop by at our kiosk any time to learn more. Viewers will learn firsthand how AI-powered workflows are enabling marketing-led transformation across the enterprise.

We can’t wait to see you!

As we approach NVIDIA GTC, we invite everyone to join us in exploring the incredible potential of AI and machine learning. From advanced workflows to immersive conversational experiences, we’re excited to provide a glimpse into how these technologies are transforming the industry now, not just in the future. We hope to see you there!

In the past, the idea of providing an automated MMM solution has terrified me. Blackbox solutions, which lack transparency, are as unsettling to me as they are to clients. However, the challenge lies in the fact that clients now demand speed and relevancy to ensure MMM thrives as it should. They require more models across their portfolio, greater granularity to account for channel fragmentation, and faster results and recommendations based on the latest campaigns and market conditions. If MMM cannot keep up with these demands, clients may resort to using easily accessible information, risking the possibility of making incorrect decisions based on inadequate data.

Therefore, I believe it is our role as experienced consultants to harness the power of artificial intelligence (AI) and machine learning (ML) to meet these needs, whilst simultaneously ensuring we still have a thorough understanding of the decisions which are being made within the process. We must guide the machine, set boundaries for AI, and sometimes intervene to provide information that the algorithms may not currently know or be able to find. AI and ML advancements should be utilized to build the core models, streamline hypothesis testing, and handle the heavy lifting. And we need to appreciate that a model itself provides limited insights. We (the consultants) must bridge the gap between the model and actionable recommendations, translating the statistics and the numbers into a language that clients understand and can implement.

The best approach combines the speed of machines with the detailed craftsmanship of the econometrician. It is a fusion of AI capabilities and the expertise of consultants that yields the most valuable outcomes. If you find yourself lacking in either aspect, I encourage you to get in touch with us. We would be delighted to discuss our approach further, ensuring that you benefit from the best of both worlds.

AI and ML offer immense potential for MMM, but they must be leveraged in a thoughtful and supervised manner. By guiding the machines, setting boundaries, and providing human expertise, we can unlock the full power of AI while ensuring accurate and actionable recommendations. Let us embrace the synergy between technology and human insights to drive success in the dynamic landscape of marketing.

For more information on how we can help with your Marketing Effectiveness measurement or Market Mix Modelling, visit our Measurement page or contact us.

First, Salesforce has announced its new product, Marketing Cloud Growth Edition, which is designed to put data at brands’ fingertips to help them grow. Second, Salesforce is extending no-cost access to Data Cloud to Marketing Cloud Engagement and Marketing Cloud Account Engagement customers with Sales or Service Enterprise Edition (EE) licenses or above, giving them access to tools they can use to fuel stronger business outcomes with Einstein 1. This includes increasing speed to market, generating more relevant content, increased conversions, and the ability to connect conversations across the entire customer relationship. Both announcements roll out to the Americas this February and the EMEA region in the second half of 2024.

Whether you’ll just be trying Marketing Cloud for the first time or are firmly established on the platform, the news has promising implications for everyone. Read on to learn what the announcements mean for your team.

Data Cloud helps brands of any size prepare and streamline generative AI capabilities.

This is an exciting time to be a marketer; generative AI has ushered in an era of marketing-led transformation and new workflows that help us do our jobs smarter and faster. According to Salesforce’s Generative AI Snapshot Survey, 71% of marketers say generative AI will eliminate busy work and allow them to be more strategic. But AI is only as good as your data; high-quality data is essential for fueling accurate models and insights in the Einstein 1 platform.

And that’s where Data Cloud comes in. No-cost access to Data Cloud opens the door for even more businesses to use the platform for the first time, helping them build a solid data foundation that will service and streamline their AI transformation journeys.

Data Cloud is quickly becoming the leading customer data platform thanks to its ability to connect across sales, services, marketing, commerce, loyalty, third-party advertising and legacy applications. Previously, Salesforce announced no-cost access for Sales Cloud and Service Cloud customers.

Marketing Cloud Growth Edition applies marketing automation to help brands grow.

The launch of Marketing Cloud Growth Edition will expand the platform’s access to the small business market for the first time. In fact, this new edition of Marketing Cloud is designed to help brands grow their business. From delivering campaigns and content faster with trusted AI to better personalizing customer relationships with data, Marketing Cloud Growth Edition applies marketing automation to help small businesses connect their teams and drive revenue on a single, intuitive platform.

Benefits of the platform include helping small teams do more with fewer resources. This means small teams can spend more time building strong data foundations—data that will be critical for successful generative AI—and leverage enterprise AI capabilities for the first time. Marketing Cloud Growth Edition removes some of the technological barriers to entry that smaller businesses face in implementing AI, helping them get up to speed with fewer headaches.

What if I’m already a Marketing Cloud user?

Marketing Cloud Growth Edition might be the cool, new kid on the block, but there’s no need to move from an existing Marketing Cloud to this one. Marketing Cloud Growth Edition indeed brings new functionality to the table, but we look forward to seeing further innovations in Marketing Cloud Engagement and Marketing Cloud Account Engagement that will bring each platform in parity with one another. This means all Marketing Cloud customers can expect more good news on the horizon.

Whether you’re an existing Marketing Cloud user or will just be getting started with Marketing Cloud Growth Edition, we’re happy to help you make the most of platform features. Having a seat on the Salesforce Marketing Cloud Partner Advisory Board and being part of the the product’s pilot program, I'm thrilled to see the platform become more accessible to even more businesses, granting them access to robust, enterprise-level data tools for the first time—especially at a time when that is so crucial to entering the new AI economy.

For those using Marketing Cloud in any of its forms, we offer guidance on how to connect your data strategy and implement features as they go live. For Data Cloud users, we can help you realize the role of data beyond the context of customer relationship management, like how to join it together with generative AI functions.

Unlock the power of AI with Salesforce.

Both of Salesforce’s recent announcements will be welcome news to marketers who are itching to ramp up their AI transformation journeys. While Marketing Cloud Growth Edition and no-cost access to Data Cloud are especially beneficial to smaller businesses, a strong data strategy is important for organizations of any size—and no matter your Marketing Cloud of choice, we can help you make the most of your customer data on the platform.

Got any questions about Marketing Cloud Growth Edition? Check out Salesforce’s announcement for more.

Among these are the successful implementation of artificial intelligence in marketing strategies, the advent of new interfaces for engaging with technology, and the creation of a new class of experiences that are more immersive and personalized than ever before. Let’s dive in!

Data foundations remain crucial for successful AI implementation.

“Enterprise clients will continue to emphasize building internal AI capabilities, which will vastly increase the demand for data and the systems required to manage it at scale,” predicts Tyler Pietz, Global EVP, Data. Indeed, a solid data foundation is the price of entry for successful AI implementation, especially as brands look beyond third-party cookies to better understand their audiences and build ownership of their data. By first creating fresh, predictive and prescriptive data streams that feed into AI workflows, brands can ensure their AI implementations are not only successful but are also self-evolving and constantly improving the accuracy of insights and predictions.

One can see this with our recently announced Monks.Flow professional managed service, which connects talent trained in AI, the latest AI tools, enterprise software and microservices into efficient, automated workflows. By integrating Monks.Flow into the Salesforce ecosystem, for example, we bring the creative capacity that brands need to personalize customer journeys at a granular level. This partnership allows us to fulfill the promise of digital: one-to-one personalization at scale.

The marketing structure will evolve to enable content at scale.

Brands are preparing for another great shift in 2024: transforming their marketing structure. “Clients are shifting from traditional models to content at scale structures. These content models continue to be bespoke, some of which are built in-house while others rely on third parties,” says Dave Carey, Global EVP, Studio & Embedded Solutions.

Carey, who has a background in helping brands spin up in-house studios and embedded services and leads the Studio.Monks, sees an opportunity to deliver a tech-first vision to brands looking to shake up their marketing structure. Rather than focus solely on the talent portion of the implementation, for example, brands can organize themselves around AI-centered workflows designed to enable seamless collaboration. “AI is changing the way content is created. Clients are looking for transformation AI agencies to help them understand and implement new ways to create content,” he says.

Marketers will aim to integrate media, content and commerce.

AI can help with far more than content creation, serving as an integrative force across content, data and media, a key goal that VP, Media Enablement - GTM New Business Victoria Milo sees emerging in 2024. Prompted by a reorganization of the media landscape—including consolidation of media partners and agencies—and a slowdown of growth in the media industry, brands will increasingly seek to solve media challenges with non-media solutions fueled by AI.

AI-powered innovations in platforms will connect customer insights and user experiences.

A brand’s own platform is a great spot to better align behavioral insights and user experience. Thankfully, digital experience platforms like Adobe Experience Manager are integrating AI features in service of these goals, says Business Lead Platforms & Ecommerce Remco Vroom, who leads the Platform.Monks. These features enable brands to apply dynamic learning capabilities to anticipate and adapt to user needs with remarkable speed and precision.

Adobe Sensei is one example, which combines generative AI with integrated workflows to deliver customer experiences at a scale previously unimaginable. Meanwhile, Salesforce is incorporating generative AI features that enable teams to produce enriched content and journeys at scale by utilizing customer data. This integration of AI within digital experience platforms will continue to revolutionize how brands respond to user needs in real time.

These features help underscore our own approach to platform development: generating actionable behavioral insights, then applying those insights to craft a superior user experience. “As we develop more intelligent digital solutions, our aim is to lead the change by establishing a new standard for digital ecosystems that think, learn, and grow. The future is performance-first, data-driven and AI-empowered," says Vroom.

The first global, AI-powered influencer will enter the chat.

Over the years, virtual influencers have, well, significantly grown their influence. What these digital humans do, say and share with their audiences are still crafted by teams of real people, much like fictional mascots of old—but this year, EVP, Global Head of Social Amy Luca, who leads the Social.Monks, expects to see a truly global, AI-generated influencer spring onto the scene. “This generative AI personality will be able to communicate in any language at scale, connect with cultures, and will be trained to be brand safe,” she says. They will likely be a lifestyle of fashion influencer, similar to Lil Miquela, but will enable a completely new level of one-to-one consumer communication at scale. Another possibility: bringing people back to life.

Marketers will elevate the role of immersive brand experiences.

Virtual humans are just one way that brands can better fuel one-to-one interactions at scale. And overall, Global EVP, Experience and leader of the Experience.Monks Jordan Cuddy expects to see brands focus more strongly on elevating consumer experiences in 2024 and beyond, citing a recent report that 71% executives plan to increase brand marketing in 2024, while only 46% intend to do the same for performance marketing.

But marketers face a dilemma: performance is easy to measure—think impressions, click-through rates and impressions—but the death of the cookie will challenge those strategies. Meanwhile, it’s harder to measure the effectiveness of an immersive brand experience. “Agencies need to be able to provide the feedback loop on ROI (loyalty, conversion, engagement, sentiment and opinion) in the shift toward more immersive experiences,” says Cuddy—an opportunity that will likely be helped by Milo’s earlier point about integrating strategies under one roof.

Emotional intelligence will be key to striking a chord with audiences.

Likewise, Head of Brand Design and Brand.Monks leader Jonny Singh sees an opportunity for emotionally resonant brand experiences in 2024. “As the trend towards personalization intensifies, brands will naturally elevate interactions to a new level of intelligence, tailoring experiences intricately to individual preferences,” he says. “However, amidst the technological wave, the emotional element remains pivotal, emphasizing the importance and power of storytelling.”

With a backdrop of global uncertainty, emotionally resonant content across the customer journey will go a long way in helping brands maintain relevance and resilience. “Brands that will come to the forefront this year will be ones that combine function and emotion, using logic and magic to think, make and create new futures, now,” says Singh.

Ambient computing will begin making its way into the mainstream.

In addition to virtual humans, ambient computing is another compelling evolution of how we will engage with technology. Brady Brim-DeForest, CEO of Formula.Monks, our technology services practice, envisions the dawn of truly pervasive and transparent software powered by AI. "I see 2024 as the beginning of the rise of true ambient computing. I think we’ll look back at the middle of the 2020s as ‘peak screen’—the future of work is coming fast and it will largely be screenless," he says. If you’ve interacted with a voice assistant on a connected speaker or wearable, then you’ve already dipped your toes into the screenless future. Now, generative AI will make these agents smarter and more reactive to user needs.

Brim-DeForest expects the way we interface with technology will evolve beyond verbal speech, as seen with emerging technologies like Neuralink. Brain implants may be a while away, but ambient computing isn’t far-fetched; in a recent episode of the Nex6 Project, Brim-Deforest explained how software has followed a trend of abstraction that will make these screenless experiences inevitable—and more natural, meshing seamlessly with our everyday routines.

AI innovation will focus less on hype, more on practicality.

Building on Brim-DeForest’s perspective on seamless technology use, Sander van der Vegte, VP, Emerging Tech and R&D on the Labs.Monks, sees an imminent shift towards more accessible and practical AI applications after a year of hype.

Van der Vegte notes a move away from the hype surrounding AI towards a more pragmatic approach that more realistic about AI's capabilities and use cases. “Its output is pretty good, but not great out of the box," he adds, creating a need for bespoke models that integrate with a brand’s production pipeline.

Here’s to the year ahead!

Time will tell if these predictions will come to fruition in 2024. Regardless, the convergence of AI, new interfaces and immersive experiences is providing new opportunities for brands to connect with their audiences in meaningful and innovative ways. Brands who successfully navigate this terrain will be those that adapt quickly, build robust data foundations, and embrace the potential of AI.

Search Generative Experience (SGE), or “generative Search Engine Results Pages (SERPs)” as I call it, serves as a facilitator for those seeking to find information on the web with greater speed. Instead of relying solely on keyword-based searches, you could pose complete questions and even follow up with additional inquiries, mimicking the conversational style of interacting with a language model-based chatbot.

However, since its launch, numerous discussions have arisen regarding this innovation—its advantages, disadvantages and potential limitations. For content marketing and SEO professionals, the question remains: what does this feature mean for our work?

What are the main changes we’ll see in the SERP?

Based on the various featured snippets and enhanced results currently available, it’s evident that the SGE will indeed greatly enhance users’ access to information. And if you are thinking, “I need a quick answer to a question, and I want it in an easily accessible place that allows me to navigate through complementary pages to delve deeper,” then Google will remain unrivaled. 

It’s like getting all you need in one search. And it makes sense, right? After all, Google held a global market share of 90.6% in June 2023, as reported by Similar Web. Additionally, according to Semrush's The State of Search, about one in five searches resulted in a click on the first search result. These are significant numbers, and when we talk about clicks in top positions, we are also referring to visits to sites that have a user-first mindset, promote quality content creation, respect the best practices of EEAT evaluations, conform to Google’s Helpful Content system and contribute to user engagement on the channel.

In terms of the interface, the biggest change brought about by SGE is at the top section of the search results page. Essentially, generative answers replace the traditional list of paid URLs, providing users with a more immersive and semantic experience.

The image below provides a clearer illustration—although it’s worth noting there are various result variations depending on the type of search, which I’ll explore below.

Let’s look at some other examples I found.

1. Informational search for a public figure

When searching for a public figure, the Knowledge Panel still appears, and the SGE asks if you want to generate something from it. As the Knowledge Panel typically offers comprehensive information about public figures or brands, as long as the information on the corresponding Wikipedia page is reliable, SGE seems to recognize that it may not be necessary to generate or synthesize further information.

2. Transactional search

In the case of a transactional intent search, the SERP is predominantly taken over by ads. Upon reaching the end of the first scroll, SGE once again prompts you to generate information but doesn’t do it automatically. Since the search query involves a transactional keyword rather than an informative/transactional or commercial one (such as “best phones to buy on Black Friday”), SGE appears to comprehend that the user intends to view prices directly. For that, the Shopping results provided are deemed sufficient.

3. Geolocated search

In this example of a geolocated search, SGE does not appear in the first tab, and organic results are not altered in any way. This is probably based on the same reasoning behind the previous example.

4. Informational search about health

 

In the case of an informative intent search, SGE generates a comprehensive answer while displaying the first three organic results as snippets on the side. This format allows users who are seeking detailed information to access a full article. This is one of the primary advantages that I envision in the Search Generative Experience scenario: users who visit blogs or similar platforms will likely be more qualified and engaged with the content they choose to explore.

5. Informational search about finance

In another search involving a hybrid intent, encompassing both informative and commercial aspects, SGE is displayed in a condensed manner, while a list of Featured Snippets offers more comprehensive results just below. However, due to space limitations, SGE requires users to click on “See more” to access the complete information. Upon expanding the view, SGE provides somewhat more generalized tips compared to the Featured results—image below.

Informational search about games

In a purely informative intent search, SGE once again appears in a condensed form, with the Ingram blog ranking as the top organic result. Additionally, a “People Also Ask” box is visible below. For SEO professionals, it is important to note that, according to data from Insight Partners, 57% of the result links mentioned by SGE are derived from the entire first page of organic results. This means that if your brand appears on that page, there is a significant likelihood that it will be referenced by the AI and consequently maintain high visibility.

How can brands prepare for SGE and succeed in this new landscape?

According to the information we have so far, the SERP will change. However, this is not the first time we’ve had to get used to changes, is it? Like other times, we are always preparing for future Google alterations. The extent to which this poses a challenge for brands depends on the quality and focus they put on SEO and content marketing.

SGE doesn’t change the core principle of SEO, which is to ensure visibility and relevance. It is important, therefore, that we see it as a new era for brands who want qualified organic visibility and are already working hard for it. It will still be very necessary to:

• Continue evolving and seeking better practices for organic ranking, focusing on content that prioritizes being user-first and responding to search intent.
• Increase care during article production, looking at expertise in the segment, optimizing features, and different ways to stand out in SGE.
• Ensure continuous and in-depth understanding of SGE, delving into concepts like Answer Engine Optimization (AEO), for instance, rather than perceiving it as a “villain” in the SEO landscape.
• Continue to adhere to the principle that content is king, and its quality will always be fundamental, with even greater emphasis on sharing authentic research and data, user-generated content (UGC), and utilizing various media formats. Incorporate linguistic inclusion, keywords from related semantic fields, and adapt to hybrid search intent. Additionally, ensure an optimized HTML structure.

To succeed in this new landscape, you have to immerse yourself in it and study it thoroughly. This is precisely what my team and I have been doing, and we recommend anyone interested in the subject to do the same. If your brand has not yet prioritized SEO, content marketing, and the essential work required to attract new users and populate the top of the funnel, now is an excellent time to do so. If needed, look for a team of specialists who can help you diagnose, detect, optimize, measure, and—of course—elevate your website to the top.

Brands often run into one of two common problems when making early moves in AI: they either understand the benefits of the technology but don’t know where to start, or they stitch together a Frankenstein’s monster of point solutions and tools that are ultimately disconnected from each other—inhibiting AI’s potential. Solving these operational challenges is our bread and butter as a consultative partner because we use AI each day—and have built our credentials in the technology over the last decade.

Integration lays the groundwork for AI transformation.

One of the major opportunities in AI is that it serves as a systems integrator, ingesting data and insights from across business units and customer touchpoints to enhance the customer experience and build new efficiencies. At least, that’s the ambition. Each element of the marketing mix—data, media, creativity and technology—must combine for AI to be deployed at its fullest potential.

In the past five years, we’ve made the case for an integrated marketing services partner who can unify each of these practices. That process has laid the groundwork for building an AI-powered, end-to-end workstream extends across and merges each of our capabilities. Our recent release of Generation AI, a formative report launched in collaboration with Salesforce, offers a window into how the technology is helping teams shape the entire marketing remit from insight to idea to execution.

Breaking silos and building a culture of experimentation have accelerated our ability to build this mature AI offering for brands. In fact, experimentation with AI has long been part of our business, with Co-CEO, Content Wesley ter Haar telling VentureBeat in 2017, “[AI] will allow us to refocus our efforts on what’s really going to impact the project in a meaningful way––which is design vision, design thinking and real creative leadership.”

But experiments in AI have long been relegated to the realm of R&D rather than the hands of everyday talent. When the generative AI boom suddenly ignited a year ago, making the technology far more user-friendly to people regardless of their knowledge in AI, our team enthusiastically rallied around Slack channels dedicated to brainstorming ways it could help them in their work.

This collaborative spirit has matured from casual experiments to innovation sprints that push tech to its limits, to products and services built bespoke for brands. Just look at our work with BMW Group, in which we built an AI-powered music creation platform that celebrated the brand’s partnership with EDM festival Tomorrowland. Music fans worldwide could create their own custom festival track by selecting different options in mood, pace and feeling, enabling creative expression on an unprecedented level.

A cohesive, end-to-end workstream beats random acts of digital.

Every brand may have a different need for AI: enhancing the customer experience, overcoming production constraints, activating customer data, or even a combination of those needs. That’s why we’ve built a flexible, AI-driven pipeline that connects a wide range of proprietary and third-party microservices across a single workstream.

In addition to making it easier to develop content at scale, the workstream critically has the potential to break down siloes between marketing and adjacent parts of the business. For example, imagine if your product design team could share 3D renders used to iterate assets that are then tested for performance, ultimately identifying the product angles and other variables in creative that best fit customers’ interest. Marrying product design, creative production, market mix modeling and customer insights, this workstream results in a flywheel that can inform future product designs and content.

"Experimenting with AI is important, but what’s more important are the business workflows,” says Michael Dobell, Co-Founder and EVP Innovation. “AI has sparked the need for workflow transformation, and we guide them through that change, unlocking performance gains, lowering costs of production and finding new ways of working." While marketing may be the most natural place for AI to make an impact right now, it’s actually a harbinger for wider business transformation—and this view, in turn, sets a new expectation for the role that agency partners will need to play to help brands get there.

For Kraft Heinz, we took a strategic approach to helping their in-house agency, The Kitchen, identify where and how AI could drive high value by increasing efficiencies, saving costs and elevating creative output. Together with the team, we developed a roadmap that walked through four key takeaways: data security, internal adoption, testing use cases and establishing adaptable frameworks. Overall, the engagement resulted in actionable, initial steps for the brand’s own internal team to take calculated steps toward AI maturity.

Here's to many more wins in the AI race.

We’ve always called ourselves a new age, new era partner to the world’s most innovative brands. Earning the title of Adweek’s AI Agency of the Year demonstrates that we’re already ahead—and just in time at the dawn of what’s been called the fourth Industrial Revolution.

See what else we've been up to with AI here.

And opportunities there are. In the last few months alone, we’ve completed three innovation sprints in collaboration with some of our key cloud partners. First, we joined forces with Amazon Web Services (AWS) to host a challenge across time zones to create internal AI tools using Amazon SageMaker. A few weeks later, Google gave us, in our capacity as a large Workspace customer, the chance to play with Vertex AI and push the technology to its limits in two multi-day events focused on experimentation.

From the outset, the purpose of these sprints is to benefit our cloud partners next to our own business, as we collaborate on solving key industry challenges, developing use cases that drive brand results, and strengthening our partnerships.

Seizing every opportunity to tweak our expertise. 

The setup of innovation sprints is as follows: together with our partners—AWS and Google in this case—we come up with a challenge. Hereafter, our talent dedicates their time and creative chops to come up with ideas and execute on them by using the partner’s AI technologies. 

The needs of brands are at the heart of every sprint. Privacy, for one, is always a bright golden thread, as most brands are highly concerned with making sure everything is safe and sound. Collaborating with AWS and Google to develop AI tools guaranteed we were operating in a privacy-safe environment within their cloud computing platforms. For instance, when you’re deploying a project to Vertex AI, it’s going to be sort of sandboxed within your own hosting environment, which means it’s only pulling data from a knowledge base that you control. As for Amazon SageMaker, this service is GDPR-compliant. 

When it comes to AI-driven projects fully hosted by our partners, our Technical Architect and one of our AWS Certified Solution Architects Ben Moody says, “We used to tackle AI projects with high-level tools like Amazon Rekognition and Transcribe, among others. With Amazon SageMaker, we can be entirely flexible, covering any custom AI solution, high AI data privacy needs, and low latency requirements.” 

In developing AI-driven solutions for brands, it’s critical to know all the capabilities as well as limitations of the tools you’re working with. As our Senior Creative Technologist Angelica Ortiz highlights, “We use a lot of the latest tools from our cloud partners, and these innovation sprints are a great opportunity to formally dedicate the time towards testing their capabilities.” Such early-stage testing enables us to truly understand the limits of what we are pushing certain tools to do—and as a result, McDonald says, “New ideas get spun around all the different ways we could use a technology, which is 100% going to show up in our client work.” 

Accelerating experimentation to drive results for brands.  

As anyone who works in the field of technology knows, experimentation has a ripple effect. Whether you run into a roadblock or discover a new possibility, you’re always expanding your knowledge and skills. But these ripples have a much further reach than just the individual creative, designer or developer. By experimenting with building our own AI tools in partnership with leading technology brands, we’re able to create truly crafted, custom-made solutions for our clients. Let’s be honest, massive AI tools can’t really do that (yet).

“With tools like SageMaker and Vertex AI being made available to us, we’re really able to supercharge our experimentation processes,” says McDonald. “And then, we can feed these generative AI learnings back into our existing projects and new pitches for AWS and Google as our clients.” As it turns out, most of the solutions our Monks come up with during these innovation sprints are transferable and can be wrapped up and applied to various other scenarios. 

Feedback is a very powerful ripple. Once a sprint comes to a halt, we always share our learnings with the aim to help our cloud partners improve their tooling. For example, Moody says, “During the AI challenge with AWS, we had ten teams with members across different time zones, and so we quickly noticed that it was not easy to set up a seamless MLOps and Monitoring strategy. Since our team was lucky to have direct contact with AWS, they supported us right away and provided learning resources for future production iterations.” 

Similarly, innovation sprints allow us to offer our cloud partners an exciting new take on their technologies. “They’ve been working on their products for years and years, so we can provide fresh perspectives—and sometimes even discover bugs in the system—by applying what we know using their tech. While they help us learn more about these technologies, we give them valuable feedback on how they can improve their products and services, so it’s really a win-win situation,” Ortiz says. And as a fun bonus, it often makes our partners excited to explore uncharted territory together.

Nurturing partner relationships is an ongoing process.  

This feeling of excitement to keep experimenting has been echoed by every participant and organizer of our recent innovation sprints, including myself. Now, all there’s left for us to do is to keep carving out the time, so that we can continually develop our creative ideas inspired by the technologies that our cloud partners kindly make available to us. Our Technical Solutions Engineer Sarah Sheppard highlighted that it’s great to “finally get the time to build some momentum on something. We have so many day-to-day things that can slow us down, so to actually set aside time and create space so we can keep our ideas moving forward—I think that's the best thing these sprints do for us.” Her team, for example, had several weeks to flesh out ideas, while getting trained on the AI tools. “This made the whole experience feel like a sprint, as we tried to do as much as we could in the allocated time,” adds Sheppard. 

Ultimately, this time spent on experimenting with existing technologies and creating new applications allows us to not only drive technical solutions for our cloud partners (and ourselves), but also push our partnerships forward. As Sheppard tells me, “One of the best parts of these sprints has been working with our partners and seeing where their heads are at in a totally different context. Instead of reaching out about a fire that needs putting out, I was now messaging them to say I had some cool ideas and if we could work on it together.” In the end, when it comes to team play, you always want to make sure that you add some fun to the game.