First, Co-CEO of our Content practice, Wesley ter Haar, has won an award in the Individual category for his role in rallying our team around AI innovation. Our collective team has been awarded in the Organization – Strategic Planning category for our accomplishments in building AI workflows designed to help marketing teams overcome a wide breadth of creative and marketing challenges. And one of those workflows was honored as well, with Monks.Flow achieving a win in the Product – Hybrid Intelligent System category, just three months shy of the service’s initial launch.

If you’re unfamiliar with it, Monks.Flow is an AI-centric, professional managed service that streamlines how humans and machines work together. News of the win comes hot off the heels of the launch of Persona.Flow, an expansion of the Monks.Flow service that provides deep consumer intelligence by simulating detailed, interactive consumer personas that marketers can engage with in real-time conversation. But overall, the trio of wins showcase the holistic efforts of our team—from individual influence to collective experimentation and innovation—to lead the industry in the AI economy.

Monks.Flow solves high-value use cases for marketers.

The powers of generative AI grow more impressive by the day, but we noticed a key perception challenge in early discussions with brand leadership: while AI-generated visuals are certainly remarkable, marketers felt that the output still lacked the kind of quality required for their specific marketing needs. We also realized that AI’s benefits went far beyond making individuals more productive; rather, automated workflows could help align business units and enable greater collaboration across teams.

We sought to address both challenges and opportunities in the development of Monks.Flow, which empowers marketers to exercise complete control over AI’s output across the life of a campaign. The service weaves together numerous workflows designed for developing insights, building assets at scale, adapting content, measuring performance and optimization and more—meaning teams can shape and influence the AI according to their precise requirements with custom brand models that are accessed in a safe and secure environment.

We continue to expand Monks.Flow to solve emerging needs with AI.

Ultimately, our goal is to streamline the ways humans and AI work together—and our latest innovation Persona.Flow takes this goal a step further, bridging the gap between brands and their customers. Persona.Flow is an interface that allows brands to speak to their data and get inside the minds of their audiences by conversing with dynamic, AI-powered personas. The core technology behind Persona.Flow is driven by a robust RAG framework that weaves together brand-owned data and factual data from market research libraries provided in partnership with data-driven marketing firm Claritas.

All of this enables brands to build up their customer insights, identify trends that resonate with consumers in real time, and act on those trends with incredible speed. Wesley ter Haar, who was also honored with an Excellence in Artificial Intelligence Award in the Individual category, compares these smart personas to digital twin technology. “Traditionally, digital twins allow you to test different scenarios, optimize existing workload and get warning signs when it comes to wear and tear. So that's quite a tried and tested concept when it comes to supply chains and factories,” he says. “Persona.Flow is a digital twin concept in which you create digital twins of your consumer base, allowing the ability to run hypotheses of your creative and marketing space.”

From workloads to workflows, we’re transforming the service model.

Monks.Flow represents another challenge that AI presents to our industry: the need to move beyond traditional, time- and materials-based business models to better reflect AI’s impact on work.

Our win in the Organization – Strategic Planning award category honors the work we have been doing to build a new service model designed for the AI economy. Others have shied away from the existential question of how you would rebuild an existing business for today’s reality, but we’ve embraced it. In pioneering a new commercial model for our industry, we’re building proven workflows that brands engage with via an SLA-based billing model that is focused on output.

Looking ahead, there’s far more innovation to come. Following the keynote at this year’s NVIDIA GTC conference, ter Haar spoke on how the presentation focused on compute as a catalyst for transformative change that shows no signs of stopping. “If you had to make the case for what is the most important accelerator for our world at the moment, it seems to be compute. We're looking at a historic upswing in the ability to deliver that at scale."

Speaking to a Digiday reporter at the conference, he noted, “I think [NVIDIA President Jensen Huang’s] point is that everything that can either be automated or done by robots will be automated or done by robots.” With the growing importance of AI in the marketer’s toolkit, and NVIDIA’s growing role in building the foundational infrastructure that underpins it, shows like GTC will make their way onto more and more marketers’ calendars, serving as further evidence of how our industry continues to evolve with technology.

Looking ahead at accelerated technological transformation.

The world keeps changing—and fast. Our wins from the Business Intelligence Group’s Excellence in Artificial Intelligence Awards underscore our collective ambition to not only improve individual productivity, but rather fundamentally transform the entire business with AI, enabling a higher degree of coordination, speed and scale for brands.

This is marketing-led business transformation at work, adapting and evolving the enterprise to better reflect the AI economy. There is no doubt that AI will continue to play an integral role in ensuring that we operate smarter, faster and on a larger scale than ever before—and we’re excited to lead the charge along every step of the way.

Eric Shamlin, our EVP, Strategic Partnerships, joined with industry veterans on the panel to highlight the exhilarating journey of experimenting with AR, VR, and AI over the past several years. His team's foray into emerging media has not only been fun but also incredibly fruitful, showcasing AI's potential to revolutionize creativity.

Together, the panel painted a picture of how AI has transitioned from a mere experimental tool to an integral part of the creative process: whether to speed up pre-production, ideate concepts, or create assets at scale, AI workflows have become indispensable for the enterprise. In fact, these technologies not only facilitate creativity but also democratize it, allowing more people to express themselves in ways previously unimaginable—while also giving creative teams the ability to reach far more diverse audiences with personalized, relevant content.

Still, the panelists agreed that the role of human touch remains key. They shared experiences where AI-generated assets underwent manual refinement to meet quality standards, highlighting that while AI can significantly enhance efficiency and creativity, it does not replace the nuanced skills of human designers and creators.

“For creators, AI gives them superpowers,” Shamlin explains. “More people can create, like my good friend who is not classically trained as a creative–he's an accountant–but he can now let his dreams run wild.”

Looking ahead, the conversation touched on potential design trends influenced by AI, such as mashup culture and a renaissance of creativity across various mediums. The panelists envisioned a future where AI empowers creators to explore new horizons without being constrained by traditional limitations.

For brand executives who are curious about incorporating AI into their operations, this discussion offers valuable insights. It’s clear that embracing AI can lead to remarkable efficiencies and unlock new creative possibilities. However, success in this evolving landscape requires a willingness to experiment, learn continuously, and adapt strategies in line with technological advancements.

As we stand on the brink of this new era in creativity powered by artificial intelligence, one message resonates strongly: the future belongs to those who embrace change enthusiastically and leverage these powerful tools to enhance their creative endeavors.

At its core, Smaller is Better dismantles the long-held belief that bigger always means better in the enterprise, presenting a compelling case for why smaller teams are, in fact, the secret weapon for achieving agility, innovation and competitive advantage in today's fast-paced market. Through a blend of rigorous research, real-world examples, and Brim-DeForest's own experiences leading our Technology Services practice, the book offers a transformative approach for organizations of all sizes to become more efficient, adaptable, and ultimately, more successful.

Whether you're a startup founder, a leader in a large organization, or somewhere in between, Smaller is Better provides a practical guide to reimagining how work is organized and executed. It invites readers to rethink leadership, collaboration, and performance, making a compelling case for the small team model as not just a strategy for success, but as a necessity for survival in the modern business landscape.

We sat down for an interview with Brady—here is what he had to say:

Your book, Smaller is Better, challenges the traditional model of large, siloed teams within enterprises. What are some of the specific drawbacks you've observed in these environments?

The drawbacks are multifaceted and deeply impact an organization's ability to innovate and respond to competitive pressures. Such teams, structured within a traditional large-organization culture, often operate in an environment that extinguishes risk and discourages failure. This risk-averse culture significantly stifles innovation, as it prevents team members from taking meaningful risks and exploring new solutions to complex problems.

Innovation inherently involves a degree of risk and failure; it requires doing things that are not fully understood or mapped out. When failure becomes anathema, team members tend to opt for safer, more predictable paths, even if they lead to suboptimal outcomes. This leads to a culture of learned helplessness, where innovation atrophies and the organization becomes less adaptable and more vulnerable to external changes and competition.

Traditional models of decision-making in large enterprises often place the power in the hands of executives who are far removed from the day-to-day operations and front-line information. This disconnection between decision-makers and the operational realities of their business not only slows down the decision-making process but also leads to decisions that may not reflect the best interests of the organization or its customers.

The "teams model" outlined in Smaller is Better challenges this status quo by inverting the decision-making hierarchy, thus empowering individual contributors and smaller teams to take meaningful risks within their specific missions. This model fosters an environment where small-scale failures are not only allowed but celebrated as learning opportunities, leading to faster innovation, improved productivity, and ultimately, greater organizational agility.

Our industry is evolving rapidly, with new trends and technologies emerging constantly. How do you see the "small teams" approach fitting into this fast-changing landscape?

The "small teams" approach is increasingly relevant and effective in the context of rapidly evolving market dynamics and technological advancements. Small team structures, contrary to being unrealistic for large companies, are ideally suited for enterprises of any size. They scale beautifully, whether the organization is managing one team or a thousand, as long as each team is aligned with an appropriately sized mission. This flexibility and scalability ensure that the basic structure and culture supporting small teams can lead to replicable success across the entire organization.

Moreover, the "teams" framework is highly adaptable, working just as well for remote and distributed teams as for those that are co-located. This adaptability proves that autonomy is a critical structure for teams, facilitating better performance irrespective of their physical work environment. Additionally, in the era of AI and other technological innovations, the move towards smaller, autonomous team structures becomes even more necessary. As teams become smaller, the use of AI tools allows them to make an outsized impact, driving organizations towards more nimble, innovative and efficient operations. The AI revolution, in essence, necessitates and amplifies the effectiveness of the small teams model, making it an indispensable approach for navigating the complexities of today's business landscape.

Let's talk about building and optimizing small, autonomous teams. How do you define and align teams around clear missions within a larger organizational context?

It involves a meticulous process that integrates the team's purpose with the organization's broader objectives. It starts with establishing a clear and compelling mission for each team, which is crucial for ensuring that the team's efforts are not only aligned with the organization's goals but also imbued with a sense of purpose and direction. This mission must be well-defined, measurable, and achievable, serving as a guiding star for the team's activities.

To ensure effective collaboration among these teams, it is vital to promote a culture of transparency and communication. This involves regular check-ins, where teams share their progress, challenges, and learnings with one another, facilitating a supportive environment where teams can learn from each other's experiences and coordinate their efforts more effectively. Additionally, leveraging collaborative tools and platforms can enhance this inter-team communication, allowing for seamless sharing of ideas and resources.

Moreover, aligning teams around clear missions within a larger organizational context requires a robust framework that supports autonomy while ensuring coherence with the organization's strategic direction. This may involve setting up cross-functional liaisons or integrating shared goals that encourage collaboration towards common objectives. By fostering an environment that values autonomy, mastery, and purpose, organizations can optimize the performance of small, autonomous teams, ensuring that they not only work effectively within their own scope but also contribute to the overarching success of the organization.

How does AI factor into the "smaller is better" approach? How can empowered, small teams best leverage AI tools to further enhance their performance?

AI plays a crucial role in enhancing the "smaller is better" approach by enabling small, autonomous teams to make an outsized impact. In a landscape where headcount is shrinking for many organizations, the integration of AI tools within team structures allows individual contributors to amplify their capabilities, automate routine tasks, and focus more on strategic, creative and problem-solving activities. This shift not only increases efficiency and productivity but also fosters an environment of innovation where teams can quickly adapt and respond to new challenges.

AI tools can help small teams analyze vast amounts of data, identify trends, and make informed decisions much faster than traditional methods, which is particularly beneficial in fast-paced industries. This ability to leverage AI effectively allows teams to maintain their agility and creativity, ensuring they can continue to deliver impactful results despite their small size. The "teams" framework, therefore, not only supports but thrives on the incorporation of AI, making it more relevant and necessary in the context of modern organizational challenges.

Can you outline a strategy for how to maintain agility as these small, autonomous teams begin to grow, scale and replicate across an organization?

A deliberate and phased approach is essential. Here is how I recommend an organization ensures sustainable growth while preserving the agility of small teams:

1. Start with success: Begin by conducting a carefully designed sandbox experiment. This initial success serves as a proof of concept for the small teams model within your organization.

2. Enlist support: After demonstrating success, gather support from stakeholders and secure additional resources. This backing is crucial for scaling the approach across the organization.

3. Limit scope: As you add new teams, carefully limit the scope of each addition. This ensures that the growth of teams remains manageable and focused on specific missions.

4. Incubate slowly: New teams should be incubated slowly and meticulously, allowing them to develop the capability to operate independently. Only after they are fully functional should more teams be introduced to the system.

It's important to move at a pace that allows teams to deeply understand their roles and objectives, learning through experience. By starting small, validating the model and expanding carefully based on success, organizations can scale their small, autonomous teams effectively, ensuring that agility and innovation remain at the heart of their growth strategy.

Your experience spans both startups and large corporations. How can leaders within established organizations, often with entrenched cultures, begin to implement the "start small" approach, especially if they lack C-suite support?

Leaders in such a situation can adopt a "start small" approach by focusing on actions that require minimal initial consensus-building and bypassing traditional gatekeeping wherever possible. An effective strategy involves empowering small teams to operate with autonomy, allowing them to directly interact with and sell to customers without necessarily seeking permission from sales or marketing departments traditionally seen as gatekeepers. This approach emphasizes the importance of agility, speed and the ability to learn from mistakes, which are critical for fostering innovation within constrained environments​​.

For leaders who find themselves in a situation where bypassing the traditional consensus is not feasible and stakeholder buy-in is necessary, the key is to frame the small teams model in terms of potential outcomes that align with the organization's broader goals. This could involve highlighting how the model will enhance quality, increase velocity or improve capabilities without committing to a specific measurable end goal within a fixed timeline. Instead, focus on selling the concept of a measurable improvement that the transformation is expected to bring about, thus aligning with the organization's overall objectives and demonstrating the potential value of the approach​​.

How are you applying the principles of "Smaller is Better" in your current role with Formula.Monks?

In my role as CEO of Formula.Monks, the Technology Solutions practice at Media.Monks, I apply these principles by tackling complex challenges with small, empowered teams. A striking example of this approach in action was when our organization was brought in to assist a two-hundred-person company that had been struggling for years to refactor their software for municipal agencies. Despite a product delivery team of over sixty people, they had made no progress and were rapidly approaching a failure state​​.

We discovered that the solution to their problem lay within the talents of just two engineers who were capable of using modern tools and moving the software to the cloud. The bureaucracy of the larger team structure was stifling these engineers' abilities to effect change. This situation underscored how larger groups can inadvertently limit innovation by adhering to the lowest common denominator, rather than leveraging the exceptional talents within​​.

By focusing on smaller, autonomous teams, we allow for greater agility, innovation and responsiveness to the unique challenges faced by our clients. This approach not only streamlines problem-solving but also harnesses the full potential of each team member, leading to more successful outcomes and transforming the way ambitious companies operate. This strategy demonstrates the profound impact of "Smaller is Better" principles, highlighting the importance of flexibility, focus and leveraging individual strengths in achieving organizational goals.

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.