1. What measures are implemented to ensure clients have control over their advertising investments across various channels?

By bringing Innovid and Flashtalking together under Mediaocean, we’ve created the leading global, independent, omnichannel ad tech platform. Advertisers will have access to a fully integrated suite of solutions, including creative personalization, ad serving, measurement, and optimization. This unified approach means they can manage and scale campaigns seamlessly across CTV, digital, social, and linear.  All data is granular and transparent, all measurement is unbiased, and advertisers are in complete control of creating a fast, efficient, powerful media supply chain as a result.

2. How does your company approach leadership restructuring following significant acquisitions to maintain operational efficiency?

The integration of Innovid and Flashtalking was designed to ensure continuity for our clients. I have taken on the role of President of the combined organization, reporting directly to Zvika Netter, CEO and founder of Innovid. This structure blends expertise from both companies while keeping us focused on a shared vision – driving innovation and delivering seamless, independent ad tech at scale that creates value for the entire advertising ecosystem.

3. In what ways does your organization address challenges associated with “walled garden” environments to provide clients with greater data transparency?

Advertisers often rely on technology owned by media sellers, which leads to walled-off access to inventory and data, less control over ad placements, and media spend optimized for publisher yield. At Innovid, independence and interoperability are core to our platform. We provide an open, scalable platform that integrates with walled-garden solutions and the open web, giving advertisers full transparency, control, and flexibility of their campaigns across CTV, digital, social, and linear. Our goal is to empower advertisers – not restrict them.

4. How do you balance the need for independent ad tech solutions while ensuring balance with major digital and social platforms?

Independence doesn’t mean isolation. Advertisers need neutral, interoperable technology that works across all platforms – not just those owned by media sellers. Our commitment to remaining unbiased allows us to collaborate and integrate with all major media platforms, ensuring frictionless campaign creation, delivery, measurement, and optimization across the ecosystem. We’re giving advertisers the flexibility to execute strategies on their own terms.  This leads to better experiences for consumers by managing frequency, understanding exposure and outcomes, and connecting the story across screens, channels and formats.

5. How does your organization ensure a seamless integration of ad serving, creative personalization, and measurement across multiple channels?

The merger of Innovid and Flashtalking brings together ad serving, creative, measurement, and optimization into a single, unified platform. By harnessing AI, automation, and a massive global dataset, we enhance end-to-end workflows, delivering more efficient, accurate, data-driven insights. This integration allows advertisers to manage campaigns across CTV, digital, social, and linear channels in one place, ensuring their messages resonate with the right audiences, in the right places, and at the right times and delivering on consumer expectations of a unified brand experience.

6. What challenges do you face in maintaining consistency when managing campaigns across digital, social, CTV, and linear channels?

One of the biggest challenges in cross-channel campaign management is ensuring consistent measurement and frequency control. Without proper management, ads can either oversaturate audiences or get lost in fragmentation. Our platform solves this by providing a holistic, real-time, and deduplicated view of campaigns, enabling advertisers to monitor reach, frequency, and outcomes across all channels. They can optimize frequency, prevent overexposure, and maximize engagement. It’s about balancing efficiency with impact to make every impression count.

1. How can brands ensure their purpose-driven marketing efforts are perceived as authentic rather than performative ?

Authenticity in purpose-led marketing comes down to one simple rule: connect words to real, measurable action.

As we wrote in our article earlier this March, brands are often perceived as opportunistic when their values aren’t backed up by meaningful initiatives. Consumers today are not just listening to what you say; they’re watching what you do.

If your brand stands for sustainability, then back it up. Earn third-party certifications. Offset your carbon impact. Switch to compostable packaging. Don’t just talk the talk—walk the walk and show the receipts.

If you’re about empowering a community—say, runners—organise a free run club. Sponsor local races. Highlight real runners in your campaigns, not just influencers in athleisure.

Here are two brands that walk the talk—and saw both trust and sales grow because of it:

1. Patagonia – Their purpose is protecting the planet. They’ve donated 1% of sales to environmental causes for decades, offer free repairs to extend product life. That level of integrity only deepened customer loyalty—and kept them growing.
   
   
2. Tony’s Chocolonely – On a mission to make chocolate 100% slave-free, Tony’s backs up its promise with traceable supply chains, fair pricing for cocoa farmers, and hard-hitting education campaigns. The result? They’ve become the market leader in the Netherlands—and they’re expanding fast globally.
   

Purpose-led marketing works—but only when purpose drives your business decisions, not just your ads. Say less, do more, and let your impact speak for you.

2. How can brands effectively communicate their values without alienating certain segments of their audience ?

Let’s start with a truth no marketer should forget: no brand can—or should—try to please everyone.

When you’re clear about what you stand for, you naturally become more meaningful to the people who share those values. That’s how you build a strong community. Trying to water down your message to avoid offending anyone usually results in saying nothing at all.

That said, communicating your values doesn’t mean being aggressive or polarising for the sake of it. It means being consistent and true to your brand’s purpose—even if that means not everyone agrees with you. The goal isn’t to divide, it’s to align with the people who care about the same things you do.

Let’s look at a few examples:

1. Veja – The French sneaker brand built its identity around ethical production, transparency, and sustainability. Their materials are sourced responsibly, and they treat workers fairly. Not everyone’s willing to pay a premium for that—but Veja doesn’t try to win everyone over. They speak directly to conscious consumers, and that focus has made them a global success.
   
   
2. Oatly – They’ve taken bold, sometimes quirky stances on dairy, climate change, and food systems. While their tone isn’t for everyone, they’ve created a loyal tribe by speaking clearly, even cheekily, about what they believe in. And they’ve sparked a bigger cultural shift in how we think about plant-based food.

The key is knowing who your message is for. Speak to them clearly. Show up for them consistently. Let the rest opt out. And accept that your brand isn’t for everyone—and that’s exactly how the most iconic brands are built.

3. What are some of the most common mistakes companies make when implementing purpose-driven marketing?

1. Saying it without doing it.
   This is the most obvious and damaging mistake. When brands make big claims without backing them up, it feels shallow. Take Shein, for example. The brand has launched a “Shein Cares” initiative and released sustainability statements, but continues to produce thousands of new items daily under questionable labor and environmental practices. Consumers are quick to spot the disconnect.
   
   
2. Overhyping tiny efforts.
   Switching to paper bags or launching a single "eco" product line doesn’t make a brand sustainable. H&M’s Conscious Collection was a classic example. It was marketed as sustainable, but investigations showed the materials weren’t always traceable or meaningfully better for the environment—and the brand continued to churn out new collections weekly. Small steps are fine, but overstating their impact damages trust.
   
   
3. Being preachy or aggressive.
   Shaming people into caring rarely works. WWF, for instance, often uses fear-based messaging that leans heavily on guilt. While the urgency of climate issues is real, there are more empathetic and inclusive ways to invite people into the cause—especially for younger audiences who respond better to empowerment than blame.

5. Treating purpose like a campaign, not a commitment.
   Purpose-led marketing isn’t something you switch on for Earth Day and forget by June. Think of brands that change their logo to a rainbow for Pride Month but don’t support LGBTQ+ causes the rest of the year, and only in certain geographies. 
6. Trying to stand for everything.
   Some companies try to jump on every trending cause—from mental health to women’s rights to climate to racial justice—all at once. The result? A blurry message that feels opportunistic. Strong brands pick one or two causes that genuinely align with their business, and they go deep. Tony’s Chocolonely, as mentioned above, focuses solely on eradicating slavery from the cocoa industry—and their consistency makes them credible.

4. What role do influencers and brand ambassadors play in amplifying purpose-driven campaigns ?

Influencers and ambassadors can be powerful allies in purpose-driven marketing—but only when they truly believe in the message.

People follow them not just for products, but for who they are. At their best, they bring reach, trust, and relatability.

But here’s the catch: they have to be the right person. Many brands partner with influencers based on follower count or engagement, not values. That’s when things backfire.

The most effective partnerships happen when:

●     The influencer is already talking about the issue (mental health, sustainability, etc.)

●     They use the product in real life (or have at least tested it properly)

●     Their audience sees the brand as a natural fit—not just an ad

A great example is Who Gives A Crap, a toilet paper brand on a mission to provide everyone in the world access to toilets and safe drinking water by 2050, donating 50% of profits to the cause.
They’ve worked with comedians, content creators, and eco-lifestyle influencers who naturally use humour to talk about awkward topics like toilets. The tone is light, honest, and consistent with the brand—pure fun, purpose-led storytelling.

Choose partners who live the values, and your message will go further.

5. How can brands measure the ROI of purpose-driven marketing beyond just financial metrics ?

Let’s be clear: financial return still matters. It’s what allows the business to grow and continue making a positive impact. Purpose and profit aren’t in conflict—when done right, they reinforce each other.

As we mentioned in our article earlier this March, purpose-driven companies can outperform competitors by up to 300%. So this is also a smart long-term strategy.

Beyond direct sales, purpose-led marketing builds trust, loyalty, and emotional connection. That’s where ROI lives in the long run.

You can track that through:

●     Brand perception – Are people associating your brand with the values you stand for?

●     Advocacy – Are customers sharing your story, tagging you, recommending you to others?

●     Talent attraction – Are more people applying to work with you? Purpose doesn’t just drive sales—it attracts better people.

●     Partnerships – Are you being invited into meaningful conversations, collaborations, or campaigns with aligned organisations?

Look at Oddbox, a food-waste-fighting veg box company. Their purpose-led messaging helped them build a highly engaged community, leading to lower churn, more referrals, and high retention—all incredibly valuable.

Purpose-led marketing is what turns customers into advocates—people who don’t just buy, but believe.

6. What industries have seen the biggest impact from purpose-driven marketing initiatives ?

Purpose-led marketing has had a major impact across a wide range of industries.

Fashion and beauty were early movers. Brands like Pangaia have built strong followings by embedding sustainability and innovation into every part of their business—from recycled fabrics to supply chain transparency. They’ve shown that consumers will pay attention when the product and purpose align.

Fenty Beauty didn’t just say it was inclusive—it launched with 40+ shades and changed how the industry approached diversity. Their purpose (beauty for all) was made real through product and casting. The result? Category-defining success.

Food and beverage has also seen big shifts. Consumers are more conscious about what they eat and drink—and where it comes from. Grind turned something as ordinary as coffee pods into a stand against single-use plastic, with home-compostable pods and a refill system at the core of the product. Since launch, they’ve sold over 100 million pods, proving that sustainability, when built into the business model, can scale fast.

Across all these industries, the pattern is clear: when purpose is real, measurable, and tied to the product—it drives not just awareness, but loyalty, advocacy, and growth.

1. Reggie, you’ve been at the forefront of cloud communications evolution. What pivotal inflection points have defined your leadership and industry outlook ?

Working in the tech and communications space for nearly three decades, I’ve seen my share of industry shifts, but two, in particular, stand out. The first, of course, is just the rapid adoption and evolution of cloud computing and its impact on how we access and share information. Initially, companies embraced cloud strategies primarily to reduce costs. However, the focus has since shifted towards more strategic benefits, including enhanced innovation agility, global customer reach, business continuity, and overall risk mitigation. We now see organizations investing in multi-cloud and hybrid-cloud environments, alongside cloud-native services like serverless architectures.

The second inflection point is the remarkable growth of AI and its use across organizations, especially in customer engagement. The technology is enabling incredible efficiencies and personalization. And our recent Global Customer Engagement Report (GCER) found a sustained rise in both the comfort with, and adoption of, AI-powered interactions within businesses. Even more interesting is the increasing consumer acceptance - and expectation - of personalized experiences and customized solutions through the power of AI. 

These inflection points have reminded me just how quickly technology evolves and the importance of continued evolution and innovation both as a company and as a leader.

2. AI and automation are redefining enterprise communication. What’s the most disruptive paradigm shift you foresee, and what’s the biggest barrier to adoption ?

No doubt AI has greatly impacted the way businesses communicate today, both internally and externally with their customers. I think the biggest shift we’re seeing, in line with our recent GCER, is that users have come to expect an element of AI to be implemented across all communications channels, whether text, voice, video, or others, so that they can achieve more personalized and efficient engagement on their channel of choice. Preference for AI-supported communication varies, with a third (32%) of consumers suggesting they’ll increase chatbot usage over the next 6-12 months (up from just 23% the year prior), just over a quarter (26%) suggesting they’ll increase voice personal assistant usage over the next 6-12 months (up from 22% the year prior), and 25% suggest they’ll increase automated phone support in the next 6-12 months (up from 21% the year prior). In terms of barriers to adoption, ensuring the technology is seamlessly integrated across these channels can be a challenge and if not done correctly, can greatly impact brand perception. Our report shows that just one bad experience would drive 75% of customers to take their business elsewhere and nearly half (48%) would leave for good after one or two bad experiences.

3. Security, compliance, and innovation often operate in silos. How can enterprises architect a framework that seamlessly integrates all three without trade-offs ?

Organizations cannot successfully innovate in today’s world without considering security and compliance. A ‘cloud-smart’ approach, which involves balancing innovation with a robust governance framework, is the smartest way to balance all three priorities. This means investing in solutions that optimize cloud costs and implementing comprehensive security measures from the outset in line with rapidly evolving regulatory standards. Additionally, adopting a Zero Trust security model is important in ensuring only verified users can access information, which is especially important when it comes to AI being used to analyze behavior and make real-time access decisions. All of this is essential to staying ahead of security and cost management challenges. 

4. Customer experience is now a key differentiator. What’s the secret to building frictionless, hyper-personalized engagement at scale ?

Building frictionless, hyper-personalized engagement at scale lies in carefully integrating comprehensive data strategies with advanced technology. The first step here is to ensure transparency in how data is being used, giving customers the chance to opt-out. From there, businesses can leverage opted-in customer data to develop a deeper understanding of individual preferences and behaviors. Utilizing technologies such as AI and machine learning allows companies to analyze this data effectively, automating the personalization process while providing real-time, contextually relevant interactions.

Additionally, creating a seamless customer journey requires a robust omnichannel strategy that integrates all communication platforms into a cohesive system. By ensuring consistency and continuity across every channel, businesses can provide a unified experience that adapts to the customer’s needs at any given moment. Continuous feedback loops and customer insights are vital in iterating and refining these strategies to meet evolving customer expectations, ultimately fostering loyalty and enhancing overall satisfaction. When customers interact with an automated system, AI can perform real-time sentiment analysis, enabling the system to escalate a call and route to the appropriate live agent when necessary. When agents receive the customer, they can also access AI-generated insights, allowing them to more quickly address and resolve customer concerns, leading to increased loyalty. 

5.With hybrid and remote work now mainstream, what’s the essential tech stack for enabling seamless, high-fidelity collaboration across distributed teams ?

In today’s hybrid and remote work environment, a thoughtfully designed tech stack is crucial for maintaining seamless collaboration. Implementing a unified communications platform helps integrate various communication channels into a single, accessible interface. For real-time collaboration, video conferencing with advanced features like screen sharing and recording capabilities is essential, alongside instant messaging platforms that facilitate quick exchanges and provide presence indicators. Our GCER found that 77% of consumers use video chat and call platforms and 91% use some kind of messaging platform, so this technology is helpful both internally and externally when communicating with both colleagues and customers. 

6. AI-powered automation is streamlining workflows, but no one wants to engage with a bot that feels transactional. How do companies strike the right balance between efficiency and authenticity ?

AI-powered automation is reshaping customer service, but striking the right balance between efficiency and authenticity remains critical. Our GCER reveals that after a negative experience, 75% of customers are likely to take their business elsewhere, and 48% need only one or two poor interactions before leaving for good. This underscores why AI-powered communication must be precise while maintaining human touchpoints. AI chatbots are evolving as essential customer service components, not to replace human agents but to enhance their capabilities. We see AI managing an increasing share of routine tasks, freeing human agents to focus on complex scenarios requiring empathy, creativity, and nuanced problem-solving. Industries like retail and finance already utilize AI for personalized support, a trend rapidly increasing with advances in generative AI and large language models. The optimal approach combines AI's efficiency with human emotional intelligence. Rather than positioning AI against humans, successful companies view AI as a tool that empowers staff to deliver exceptional, authentic customer experiences while handling higher volume interactions efficiently.

7.  Delivering seamless omnichannel experiences is the gold standard, yet many companies still struggle with fragmentation. Where do most go wrong, and how can they fix it?

Many companies struggle with delivering seamless omnichannel experiences due to a lack of integration across multiple customer touchpoints, resulting in a fragmented customer journey. This usually stems from disparate systems and data silos that prevent a whole view of the customer. Companies frequently fail to align their communication channels, focusing on individual channel optimization rather than a holistic strategy.  

To address these issues, businesses can prioritize integrating communication channels and systems by adopting an integrated, single platform approach to their communications solutions. As providers, we need to simplify multi channel availability. At Vonage, we’ve taken the one platform approach. We want it to be less about the solution and more about the capabilities - one intelligent platform that does it all.

A single-platform approach eliminates silos, improves efficiency, and enhances the overall user experience. By incorporating AI-driven automation, virtual agents, and intelligent call routing, a fully integrated UC and CC solution - for example - empowers businesses to optimize customer interactions while reducing operational complexity and costs.

8. If you had to place a bet on one emerging technology that will be the next big disruptor in cloud communication, what would it be and why ?

The rapid evolution of AI in the contact center continues and we’ll continue to see AI take more of a front seat in how agents work, augmenting the human touch with more authentic and autonomous AI-powered actions. 

Agentic AI and Knowledge-based AI - these emerging technologies operate autonomously, enabling end-to-end problem-solving teams and workflows. Designed to work like a human employee, Agentic AI will enhance CX with virtual agents that have the ability to make decisions, learn, and act autonomously - but the ability to switch to a live agent when needed will be critical. Finding that balance between technology and the human touch is still going to be very important.

1. How does AI consulting help companies bridge the gap between AI potential and practical implementation ?

One of the key challenges with AI technology, different from other new technologies, is that it doesn't have an innate purpose. Similar to how electricity is only useful when powering equipment, artificial intelligence must be paired with specific tools or tactics in order to be useful.

That's where a consultant can prove invaluable.

An AI consultant not only understands how to use AI in a variety of ways, they understand business processes, teams, and policies, and can help business leaders identify bottlenecks, deficiencies, and inefficiencies. Those are the challenges in a business that must be addressed, and adept consultants will then recommend specific applications of AI, whether generative AI or specific AI-powered tools, which can solve those challenges.

Once solutions have been identified that align with business goals, AI consulting then goes further and helps with implementation which, more often than not, consists of essential team training. It is only through AI literacy that businesses are able to truly implement AI and achieve real ROI from their efforts.

2. How do AI consulting and training services help companies create a culture of AI-driven innovation ?

The beauty of AI technology is that, once someone fully grasps what's possible and begins to apply AI solutions to their work, it's like a dam is opened within their mind and they'll see more and more opportunities. Whether that's helping with routine tasks like drafting emails or generating stock images, or more advanced workflows and automation.

The problem with many businesses today is that, while there may be several individuals in the organization learning about AI, they're doing it on their own, in silos. They aren't receiving training - in fact, just 34% of early career professionals reported receiving training in a recent survey - and they aren't actively participating in the sharing of knowledge internally. This results in inconsistent application and advancement of AI solutions, with the majority of employees being left behind. This not only impacts them negatively individually, it also represents a tremendous loss of opportunity for the business.

However, when adequate training and AI consulting are brought to the fore, not only does every employee within the organization benefit from directed learning about AI and familiarity with AI's potential, it creates an exponential effect of AI-driven innovation. As each individual learns and applies and innovates within their own circle of influence, and those innovations are shared with the rest of the organization through meetings or internal communication channels, it spurs ideas in others, invites improvements, and fosters collaboration.

For instance, when I shared with my team my process for building out new podcast interviews, the step-by-step set of custom instructions I had programmed my AI assistant to walk through, even though no one else is podcasting they learned how to build custom instructions and that it was possible to create a collaborative workflow with an AI.

3. What role does AI play in decision-making and business strategy, and how can employees adapt to this shift ?

AI itself can become an invaluable consultant and assistant, particularly for decision-making and business strategy, once someone has initial training and familiarity with core concepts like prompt engineering. Imagine having access to a paid consultant 24/7, there to answer any question and brainstorm any topic, and one who is entirely familiar with you, your business, your industry, your audience, and even your personal goals and challenges.

All it takes is an understanding of how AI works, how to customize a particular large language model (LLM) like ChatGPT or Gemini, and what information to provide it. Once done, the user has an AI assistant... kinda like a work buddy... who knows all about you and your role and what you're trying to accomplish. Which means that you can jump into a new chat and rather than trying to craft the perfect prompt that has all the context and AI might need, you can just get right to the core of what you want to talk about.

I turn to my AI Chief of Staff multiple times a day with questions ranging from simple email responses or social posts, all the way up to long term business strategy and advice - something that's critical for solopreneurs, but also anyone in any role where they lack a mentor or confidant. Just as organization-wide AI literacy can help propel an entire business, empowering everyone in your organization to have an AI strategist at their beck and call can be transformative. To help, I created a free set of instructions and prompt that anyone can use to build their own AI Work Buddy, with an optional course and community they can leverage if needed.

4. How can small and mid-sized businesses leverage AI without significant infrastructure investment ?

SMB owners should focus on all of the ways that their entire teams can leverage the LLMs before pursuing implementing new AI-powered tools and solutions. In fact, every organization that is already paying for Google Workspace has access to Gemini Advanced and should make sure every employee in the organization is trained on how to use Gemini and how to take advantage of the AI that's already integrated into so many of their other apps, like Gmail, Google Drive, and so on.

With Gemini, teams can take advantage of Deep Research to have the AI scan and summarize dozens and dozens of websites to research whatever topics are of interest. This is terrific for content creation of course, but also think about how such an application can power competitive research, market research, product research, and general business strategies. They can also use NotebookLM to create a repository of company documents and information that can then be easily summarized and questioned without having to read through hundreds of pages of PDFs, and without concern for hallucinations. And teams can share prompts and ideas for Gems (Gemini's custom instructions) which anyone can use to automate and improve whatever processes they're working on.

Businesses who aren't already paying for Google can, of course, invest in ChatGPT or Anthropic's Claude for low monthly fees, even for entire teams, giving everyone access to incredible AI capabilities.

Those are the major "closed" and premium LLMs. There are also "open" LLMs like Llama which businesses can consider, so long as there's at least one individual in the organization familiar enough with open source AI to understand how to install, configure, and make available such a company-wide solution. This approach is ideal for organizations that want to leverage AI for conversations and use-cases that might require access to sensitive or private information, such as custom records or financial data, which should never be shared with an LLM like ChatGPT.

If an SMB never implemented another AI solution, and even if the existing LLMs stopped improving and iterating, company-wide adoption of "basic" AI like ChatGPT or Gemini would still advance the company's efficiency and capability tremendously.

5. How can businesses ensure ethical and responsible AI use while scaling their AI initiatives ? 

When it comes to ethical and responsible AI usage, there are several factors to keep in mind, and how applicable each of these are depends on the business and use-case. 

a. Transparency - While we're in the midst of this AI Revolution, there are still qualms and concerns in some sectors and scenarios about the use of AI, so instances where AI is being used to generate information or take actions that are externally focused should be 100% transparent about their use of AI. This can include marketing, sales, customer support, services, and more.

b. Bias - Because AI models were trained on existing data and information that existed on the internet, there exists tremendous bias. This is most commonly seen in content where women and minorities are dramatically underrepresented and therefore must be accounted for. Beyond that, businesses need to be aware of the potential for bias in data and not rely on AI-powered conclusions without first considering how those conclusions were reached and whether they were unduly influenced. A basic example might be if you were to provide your AI with a month's worth of website traffic and ask for an analysis on your audience, without telling the AI that you paid for a Meta ad for 7 days that drove an unusual amount of traffic from EMEA. The AI would come to the incorrect conclusion that your business is growing in that region.

c. Copyright - Today's laws do not protect the copyright of AI-generated content of any kind, though they're moving in that direction. Which means if you use AI to create an ebook for your business, or on behalf of a client, that work may not be protected. Businesses must be mindful of this and ensure that if a piece needs to be protected by copyright law, it cannot be wholly created by AI.

Most importantly, it is imperative that business owners adopt a policy of company-wide AI literacy and provide adequate training. Not only can this help ensure responsible AI use by all, it also helps ensure that every individual in the organization is afforded the opportunity to upskill with AI and protect their career.

6. How does AI training empower employees to work more efficiently rather than fear automation ? 

That is the underlying concern today, isn't it? That AI will take my job or your job. And while there has been a lot of hype and debate on both sides of that argument in recent years, the truth is simple: some jobs and tasks will no longer need to be done by humans. Some roles and careers will be replaced by AI, whether that's AI-powered systems or AI-equipped employees who simply perform the same tasks faster or better than non-AI using employees once did.

The World Economic Forum predicted that by 2030, 92 million jobs would be displaced by AI, and that 170 million new jobs would be created. Governments and Big Tech were happy to see more than 78 million new jobs could be created, but that still means 92 million people need to upskill or reskill.

Just as with every past Industrial Revolution, this AI Revolution will result in some jobs simply no longer being needed, but the good news is, AI as a technology and skill is one that anyone can adopt and learn. Because Generative AI is conversational, one doesn't have to have a PhD to leverage it. Far from it, in fact.

With a basic level of AI literacy, any employee can use AI and discover ways that it can make them more efficient in their role and more productive for their companies. They can also then envision tasks they were doing which AI can do today, and other or even new tasks they're now freed up to focus on. Because, let's be honest... we all have tasks or aspects of our job which are boring, mundane, and repetitive. Why not figure out how to hand most or all of those tasks over to an AI system to handle while we then have more time in our day to think strategically or re-focus on the more creative and interesting aspects of our job?

Rather than being overwhelmed with countless mindless tickets, let AI automate the most repetitive customer support queries and give your staff more time to spend with high level customers and complex problems.

Rather than wasting time emailing status updates and meeting notes, let AI handle that while your team focuses on actually moving projects forward and doing the necessary work.

Rather than mindlessly clicking back and forth through countless websites trying to find answers to an obscure question, just ask AI for the answer and source, then move on with your day.

AI can be incredibly empowering and enlightening for every member of every organization. The first step is to educate each employee on what AI can do and what it represents to them, and their role. That's why AI literacy and training should be a top priority for every business today.

1. How does the adoption of tools like MarketingGrader.AI impact the efficiency and effectiveness of marketing campaigns ?

You can’t know where you’re going unless you know where you’ve been. MarketingGrader.AI is a tool to help you understand where you’re at, what’s working well, what’s not working so well, and opportunities for improvement. With over 500 data points across eight different marketing categories, MarketingGrader.AI is the most robust tool on the market to help you measure the overall effectiveness of your marketing campaigns. Through the insights in MarketinGrader.AI, your organization can quickly create a roadmap to more impactful and effective marketing.

2. What challenges might businesses face when integrating AI-driven tools into their marketing workflows, and how can they overcome them ? 

I think the biggest challenges of integrating AI is truly understanding their place. AI isn’t meant to replace people. It’s meant to make people better. I think it’s well accepted now that if you’re not using AI in some capacity, you’re losing. But you can also lose with an overreliance on AI. Each company has to find that balance of utilizing AI to speed up processes, come up with new ideas, improve and measure your metrics, and even draft initial content, but without a human reviewing, training, and expanding on AI, it’ll never be as effective as it could have been.

3. How can AI-powered tools assist in optimizing various aspects of marketing, such as SEO, content strategy, and social media engagement ?

There are so many amazing AI tools out there that can help in these different areas. But for me, the first step is to understand how you’re currently performing. SEO for the sake of SEO does no one any good. Content for the sake of content is a waste of time. Social media posts without a clear plan and KPIs is just noise. Using AI to get data on your current state of each of these areas and then using AI to improve, expand, and research for you can make all the difference.

4. What role does data quality play in the effectiveness of AI-driven marketing tools ?

I think it’s everything. AI on its own isn’t helpful. AI has to be trained. You have to take the time to feed the model information, data, and content that represents your brand and the content that you want it to produce. AI has been known to have hallucinations and make up things that it doesn’t know. And it does it convincingly. There is still a major risk of publishing inaccurate or completely false information through AI if you don’t take the time to ensure that the data and information that it’s serving you is accurate and correct.

5. How can businesses measure the return on investment (ROI) when utilizing AI-based marketing optimization tools ?

If done right, I think the ROI on AI should be measured in man hours. It is meant to save us time and also create a collaborative experience, even for a team of one. The time savings as well as the impact of the content that AI produces all should be factored into the overall return on investment of any AI tools that you utilize.

1. How can brands measure ROI in influencer marketing beyond metrics like likes and shares ?

Likes and shares are surface-level. The real value lies in conversions, brand lift, and cost efficiency. ROI should be measured by how many people actually take action-clicks, sign-ups, sales, or even brand recall over time. I’ve seen campaigns where the cost per engagement was low, but the impact was massive in terms of customer retention and long-term value. That’s the ROI that matters.

2. What role does data analytics and AI play in optimizing influencer campaigns for maximum impact ?

A huge one. I personally use AI tools to track engagement trends, audience behavior, and ad performance in real time. Data shows you what’s working and what’s just vanity. AI helps optimize the timing, placement, and creative elements so you’re not just shouting into the void-you’re speaking to the right people at the right time. It’s like having a digital sixth sense.

3. What are the best practices for selecting the right influencers to maximize campaign success ?

Relevance over reach, every time. The right influencer is someone whose audience trusts them, not just follows them. Look at engagement rates, comment quality, content consistency, and how aligned they are with your brand’s voice. And most importantly, ask: “Would this person actually use our product in real life?” If the answer is no, it’ll show.

4. What strategies can brands use to ensure long-term influencer partnerships instead of one-off campaigns ?

Build relationships, not just transactions. Treat influencers as creative partners, not ad slots. Involve them in the storytelling process, give them space to speak authentically, and focus on long-term value. Also, track their performance holistically-some influencers may not spike in numbers immediately, but they build loyalty over time. That’s gold for a brand. 

5. How can businesses use micro-influencers vs. macro-influencers to drive higher ROI ?

It’s not either-or-it’s about strategy. Micro-influencers drive hyper-targeted engagement, especially in niche markets. Macro-influencers bring scale and awareness. I recommend a hybrid approach: use micro-influencers for conversions and macro-influencers for brand storytelling. The key is coordination and consistency. When done right, it creates a powerful ripple effect.

6. What are the biggest challenges in influencer marketing today, and how can brands overcome them ?

Authenticity fatigue and inflated costs. Audiences are smarter now - they can spot forced content from miles away. Also, some brands overpay for reach without real results. The solution? Vet influencers properly, focus on genuine alignment, and use performance data to guide decisions. Influencer marketing isn’t dead - it just needs to be smarter, not louder.

1. Why is data collection still such a challenge for organizations ?

Organizations are collecting more data than ever-captured by different teams, using different tools, for different purposes. For many, spreadsheets and manual data tasks are just as common as digital tools and automated processes.

As more teams collect more data and introduce more tools, integration, quality, and security challenges mount. When data gets stuck in silos, errors go unnoticed, compliance risks increase, and teams struggle to maintain a reliable source of truth. That’s why a structured approach to data collection is critical-ensuring systems work together to provide accurate, accessible insights.

2. How does all of this incoming data impact quality ?

Integration challenges make it difficult-if not impossible-to establish and maintain a single source of truth. What often begins as a quick fix-adding a tool here, a plugin there-can quickly turn into a patchwork of disconnected solutions. Each tool may solve an immediate problem, but together, they create inefficiencies, manual workarounds, and increased security risks. Instead of centralizing data, organizations end up with fragmented systems that prevent teams from accessing a complete and accurate picture of their customers.

These inefficiencies lead to poor data quality, which affects every stage of decision-making. Clean, accurate, and timely data is essential for identifying both roadblocks and opportunities, yet many organizations unknowingly operate on outdated, inconsistent, or incomplete data. Without a single source of truth, they may not even realize the extent of the issue, why it’s happening, or the true impact on their operations.

3. You’ve mentioned security and compliance a few times. What’s leaving organizations vulnerable ?

We recently surveyed 400 data professionals, and 91% said security keeps them up at night. And for good reason-IBM estimates that the average cost of a data breach in 2024 was $4.88 million.

One of the biggest vulnerabilities with data is a lack of clear ownership. When there’s no alignment on who owns data and how it should be managed, teams operate in silos, policies become inconsistent, and accountability slips—creating an environment where security and compliance risks thrive.

Moreover, more than half of the professionals we surveyed reported challenges with data integration and analysis. Without a clear data flow, employees resort to workarounds-exporting sensitive information into spreadsheets and sharing it via email. This disrupts workflows, increases compliance risks, breaks the chain of custody, and makes audits nearly impossible.

4. Organizations want to automate more processes, but getting there can be a real challenge. Why ?

System limitations, knowledge gaps, and budget constraints are common roadblocks. But even when automation is in place, broken integrations or homegrown solutions that weren’t built to scale can prevent data from flowing correctly into CRMs and other core systems.

Ultimately, it always comes back to the data. A structured approach to data collection is the foundation of any successful automation strategy. Once that’s in place, organizations can integrate their systems more effectively, eliminate redundancies, and reduce inefficiencies. From there, automation can be implemented intelligently-replacing manual processes where they make the most impact while maintaining human oversight where it’s needed.

5. Data quality is key to effectively adopting AI solutions as well, right ?

Absolutely. AI is only as good as the data it processes. Without structured, accurate information, AI doesn’t enhance efficiency-it amplifies mistakes. When AI-powered tools are fed incomplete or inconsistent data, they generate unreliable outputs.

AI thrives on high-quality inputs. Clean, well-structured data enables AI to automate tasks effectively, deliver meaningful insights, and optimize decision-making. But without a strong data foundation, even the most advanced AI tools will struggle to deliver real value.

1. How can integrating a DSP-agnostic platform streamline operations and reduce costs for advertisers and brands ?

Day to day, a DSP-agnostic platform simplifies operations by allowing marketers to activate all biddable media from a single UI and workflow. This saves hours of time and frustration for teams that are used to juggling multiple platforms. Instead of logging into different systems, managing various interfaces, and reconciling separate reporting structures, everything is streamlined into one place. More strategically, a DSP-agnostic approach makes it easier to test new platforms, data providers, and audience segments. When new opportunities arise, teams can evaluate them without going through lengthy legal contract negotiations or spending time learning an entirely new system just to try a different strategy. This lowers the barrier to entry for testing outside of primary partners. From a cost perspective, ensuring that media runs in the right places with the best targeting and audience data maximizes ROAS while minimizing waste. Ultimately, this leads to more efficient marketing spend and better overall performance.

2. What impact does a DSP-agnostic platform have on data consolidation and audience targeting capabilities ? 

Anytime you lower the barrier to testing and scaling new solutions, the best strategies get adopted faster. In a DSP-agnostic environment, the size of existing players matters less while the quality and value of data take the lead. Advertisers can consolidate data more efficiently, gaining better audience insights and more precise targeting. A great thing for advertisers and the rest of the industry!

3. How might the adoption of DSP-agnostic solutions affect relationships between advertisers, agencies, and technology providers ? 

We don’t expect major shifts in core relationships between advertisers, agencies, and technology providers. The real change will be in how easily all three can work with new partners. Agencies can better serve clients they previously couldn’t, advertisers can test new mediums or data providers without the usual hurdles, and tech providers can expand their reach in ways that weren’t possible before.

4. How is the shift towards DSP-agnostic platforms influence the future landscape of programmatic media buying ? 

A DSP-agnostic approach creates a more efficient marketplace by giving marketers (whether agencies or brands) expanded access to inventory, data providers, and audiences. This ensures that the best value wins more often, and media plans can be more complex without the extra work.

5. What are the potential implications of DSP-agnostic platforms on the evolution of media buying strategies in the coming years ? 

It means more channels, more strategies, and more testing. When marketers spend less time dealing with platform limitations and have easier access to inventory and data, they can focus more on strategy. This leads to more diverse, data-driven media plans that continuously evolve.

6. What role do DSP-agnostic platforms play in addressing challenges related to transparency and brand safety in programmatic advertising ?

Taking advantage of solutions and strategies to better understand your ad spend requires time, money, and the ability to interpret different measurement models - MMM, third party attribution beyond the platform buying in, attention metrics, among others. The easier we make it for marketers to integrate and analyze additional solutions to measure the effectiveness of their spend, the better we can shape the ecosystem around what our clients consider transparent and brand safe.