Agentic Commerce

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The emergence of AI agents capable of making autonomous purchasing decisions is reshaping the payments landscape. Agentic commerce—where artificial intelligence systems act on behalf of consumers to discover, negotiate, and complete transactions—presents both extraordinary opportunities and complex challenges for the payments ecosystem.

The Promise and the Problem
AI agents are poised to transform commercial transactions. Unlike traditional e-commerce where humans click through checkout flows, agentic commerce enables software to make purchasing decisions based on learned preferences and sophisticated algorithms. An agent might automatically reorder groceries, negotiate insurance rates, or book travel that optimizes for cost and convenience.
For payments providers, this opens remarkable opportunities. Transaction volumes could multiply exponentially as agents handle routine purchases. Micro-transactions become viable without human approval friction. Agents enable dynamic pricing and real-time optimization of payment methods based on rewards or exchange rates.
The fundamental challenge is determining when an AI agent has legitimate authority to spend money. How do we verify that a transaction genuinely reflects the owner’s intent rather than a hallucination or compromise? Current authentication frameworks were designed for human-initiated transactions, making Strong Customer Authentication and similar regulations problematic when software makes dozens of autonomous daily decisions.
Liability and Trust
When an AI agent makes erroneous purchases—ordering 50 pounds of bananas instead of 5—who bears responsibility? The consumer, agent provider, or merchant? Payment networks have chargeback systems for traditional commerce, but these assume human decision-making. New frameworks must distinguish between agent errors, consumer miscommunication, merchant misconduct, and system compromises while balancing consumer protection with practical adoption.
Effective AI agents require extensive data about preferences, habits, and financial constraints. Payment providers will have unprecedented visibility into purchasing patterns and AI decision-making logic, creating significant privacy risks. Questions about data portability and preventing manipulation of agent behavior will shape competitive dynamics.
Infrastructure Evolution
Payments infrastructure must evolve substantially for agentic commerce. Current latencies acceptable for humans become problematic for agents making rapid decisions. Real-time payment rails may become essential rather than premium features. Standardized APIs will be critical for agents to discover payment options and execute transactions across diverse merchants—without them, the ecosystem fragments.
Fraud detection systems currently identify anomalous human behavior patterns. When AI agents routinely make purchases across geographies or categories, these signals become unreliable. Payment providers need new approaches that distinguish legitimate agent behavior from compromised systems, creating a complex dynamic where machine learning monitors other machine learning.
Regulatory Challenges and Opportunities
Regulators are only beginning to address agentic commerce. Existing consumer protection laws assume humans make purchasing decisions with conscious intent. Anti-money laundering and Know Your Customer requirements were designed for people, not software agents. New frameworks must address agent transparency, consent, and accountability without stifling innovation or pushing commerce into unregulated spaces.
Despite these challenges, agentic commerce creates tremendous innovation opportunities. Companies solving authentication could enable new business models. Payment networks adapting fastest to agent-driven patterns could capture disproportionate value. AI could make payments more inclusive by helping consumers optimize choices and navigate complex fee structures.
Building the Future
The transition to agentic commerce will be gradual. Early adoption will focus on low-risk, high-frequency transactions like recurring subscriptions and routine household purchases. As trust builds, agents will handle higher-value and more complex transactions.
Success requires collaboration across payment networks, financial institutions, technology companies, merchants, and regulators to establish standards and build protective systems. The companies viewing agentic commerce as partnership opportunity rather than threat will thrive.
The convergence of AI and payments represents a fundamental shift in commercial infrastructure. While challenges around authentication, liability, privacy, and regulation are substantial, they’re not insurmountable. By approaching these issues thoughtfully and collaboratively, the industry can unlock agentic commerce’s potential while protecting consumers. The question isn’t whether AI agents will reshape payments, but whether we’ll build that future thoughtfully or haphazardly.

AI Won’t Transform Your Business — Change Management Will

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Everyone’s talking about AI. Few are talking about the harder part: getting people to actually use it.

The truth? AI is less about algorithms and more about adoption, trust, and alignment. Without change management, even the most sophisticated AI project can fail.

🔎 Look at IBM’s Watson Health — billions invested, but it stumbled because clinicians didn’t trust the tool, workflows weren’t adapted, and expectations weren’t managed.

🔎 Or Humane’s AI Pin — hyped as the future of wearable tech, but employees’ warnings and user readiness were ignored. The device launched without cultural or customer alignment, and it quickly collapsed.

Both examples highlight a simple fact: technology without change management doesn’t stick.

Here’s what effective AI change management looks like:

Clear vision & leadership alignment → Tie AI to real business outcomes, not experiments. Communication & transparency → Help employees understand the “why” and the “how.” Skills & training → Equip people to succeed alongside AI, not feel replaced by it. Governance & trust → Build frameworks to address bias, ethics, and accountability. Continuous feedback loops → Listen, iterate, and scale responsibly.

This is why hiring an AI + change management SME is becoming essential. They bridge the gap between technical possibility and organizational reality — ensuring your investment drives ROI, adoption, and long-term impact.

🚀 Bottom line: AI won’t transform your business on its own. Change management will. Companies that recognize this will thrive. Those that don’t? They’ll end up as cautionary tales.

The Automation Journey for Marketers and Product Managers

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Automation is no longer a novelty — it has become table‑stakes for both marketing and product teams.  The rise of powerful machine‑learning (ML) and artificial‑intelligence (AI) capabilities means that any organization that relies solely on manual processes will be at a disadvantage.  In this post we explore why automation is so important for marketers and product managers, how it helps them work together more effectively, and the practical tools (including Zapier) that can bring these benefits to life.

Why automation matters for marketing teams

Modern marketing spans multiple channels (email, social media, web, SMS and more), and the expectations for personalised experiences are higher than ever.  Automation tools allow marketers to keep pace and deliver tailored messaging without burning out.  According to a 2024 guide from the Digital Marketing Institute, the primary benefits of marketing automation include:

Time and cost savings:  Automation platforms take over repetitive tasks such as sending emails, scheduling social media posts and managing contact information, freeing marketers to focus on creative, strategic work .  Automated workflows also deliver real‑time analytics that highlight what’s working and what isn’t, enabling teams to optimize their campaigns and lower operational costs . Cross‑departmental collaboration:  Marketing automation tools improve communication between sales and marketing.  Integrated platforms provide sales‑enablement features that allow marketing teams to nurture leads with targeted campaigns, content and communications, fostering alignment across teams . Better budget allocation:  By automating routine work and surfacing actionable data, teams become more productive.  This efficiency allows marketing budgets to be reallocated toward campaigns that produce greater returns , which is vital as marketing budgets continue to shrink . Precise audience targeting:  Automation enables real‑time monitoring of user behaviour.  Platforms can track engagement and automatically segment audiences based on past interactions, delivering personalized communications when recipients are most likely to engage .  This data‑driven targeting increases both return on investment and customer loyalty. Consistent branding:  Automated systems ensure that visuals, messaging and tone stay consistent across channels.  The result is a cohesive brand presence that stands out in saturated digital environments .

Importantly, automation does not replace marketers.  As DMI notes, “automation is not about taking marketers’ jobs away… it simply enhances existing capabilities” .  When routine tasks are automated, marketers can devote more energy to creativity, strategy and storytelling.

How automation empowers product managers

Product managers (PMs) are responsible for guiding a product from vision to launch and beyond.  They rely heavily on data to make decisions, but manually collecting and analysing this information is time‑consuming and often overwhelming.  AI‑powered automation tools give PMs a powerful assist by:

Processing and analysing massive datasets:  Product management has evolved from guessing to data‑driven decision‑making.  AI and automation enable PMs to digest large volumes of quantitative and qualitative data quickly, spotting market trends and customer preferences that would be difficult to identify manually .  AI‑driven analytics can build detailed customer profiles, revealing pain points and purchasing habits, which helps tailor both product features and marketing strategies . Streamlining product development:  AI can analyse historical data and market signals to recommend product features, design elements and pricing strategies, speeding up decision‑making while reducing the risk of launching products that miss the mark .  It also aids in forecasting demand and optimizing resource allocation, resulting in cost savings and higher profitability . Enhancing decision making through predictive analytics:  Productboard notes that AI’s predictive capabilities allow PMs to anticipate future trends, customer needs and potential challenges.  Machine‑learning models can forecast demand, optimize inventory and inform product roadmaps . Personalization and customer engagement:  AI can automate the analysis of user behaviour and sentiment to deliver personalized features and recommendations.  This level of customization improves customer satisfaction and loyalty .  AI‑powered chatbots and virtual assistants also provide 24/7 customer support, reducing the burden on human teams . Automating routine tasks:  Like marketers, PMs spend much of their time on repetitive work such as collecting customer feedback or compiling reports.  AI tools automate these processes, freeing PMs to focus on strategy and creative problem‑solving . Assisting in product discovery and idea generation:  During product discovery, AI systems can conduct market research, perform sentiment analysis and segment customers to identify unmet needs .  They can also generate and validate ideas, build rapid prototypes and conduct real‑time competitive analysis .

These benefits explain why AI and automation are transforming product management.  A 2023 UXmatters article points out that by injecting data‑driven insights into strategic planning, AI enables product managers to allocate resources more effectively and improve customer satisfaction .  However, the same article emphasizes that AI is not a silver bullet; product managers must still bring human intuition to creative decisions and remain vigilant about data privacy, bias and technical implementation challenges .  Successful organizations therefore view automation as a supplement to human expertise, not a replacement .

Unifying workflows with tools like Zapier

Zapier’s value lies not just in its number of integrations but in its flexibility.  By reducing context switching and automating data hand‑offs, it helps marketing teams scale personalized, AI‑driven campaigns across multiple channels .  Product managers also benefit.  A 2024 guide to efficiency tools for product managers notes that Zapier “boosts productivity by allowing PMs to connect all of their team’s apps and services… without any coding” .  By automating the flow of information between project management platforms, feedback tools and analytics dashboards, PMs can maintain a single source of truth and focus on high‑value decisions.

Zapier is just one example.  The marketing automation landscape features platforms like Marketo, HubSpot, ActiveCampaign and Customer.io; each offers features such as omnichannel campaign orchestration, audience segmentation, lead scoring and AI‑driven content personalization .  Similarly, product teams use tools like Productboard, Airfocus and Zeda.io for roadmapping and feedback management .  The common thread among these tools is that they automate away the busywork of data collection and integration, leaving human experts to apply judgement and creativity.

Challenges and considerations

Automation is powerful, but teams must be thoughtful about how they implement it.  Key considerations include:

Data privacy and ethics:  The UXmatters article warns that massive volumes of customer data raise privacy concerns and compliance obligations (e.g., GDPR).  Product managers and marketers must balance the quest for insights with ethical data usage . Human intuition and creativity:  AI can process data and suggest actions, but it cannot replicate human insight.  UXmatters notes that product management often requires creative leaps that aren’t obvious from statistics alone .  Automation should support, not replace, the human role. Technical barriers and integration challenges:  Implementing AI and automation requires technical skills and integration with existing systems.  Teams may need to invest in training and cross‑functional collaboration to overcome these hurdles . Bias and accuracy:  AI models are only as good as the data they learn from.  Biased or incomplete training data can lead to biased decisions and inaccurate recommendations .  Ongoing monitoring and human oversight are essential.

Conclusion

Automation is reshaping marketing and product management, not by replacing human professionals but by augmenting their capabilities.  For marketers, automation drives efficiency, improves collaboration with sales, optimizes budgets and enables precise audience targeting.  For product managers, AI‑powered automation turns mountains of data into actionable insights, streamlines development and fosters innovation.  Tools like Zapier make these capabilities accessible by connecting thousands of apps, layering AI into workflows and eliminating manual data entry.  As organizations continue to adopt automation, the key to success will be balancing technology with human judgement, upholding ethical data practices and fostering a culture that embraces continual learning and experimentation.

Embracing Innovation in Payments

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As I am keeping up to date with everything happening in the Payments landscape today it occurs to me that innovation is much more than a “aha moment” that a single person comes up with. For innovation to truly occur it requires team efforts and for people to embrace it and advocate for it.

Case in point – Artificial Intelligence – its been around since the 1950’s but has only really started flourishing within the last 10 years due to the speed of technology and expansion of data. What’s amazing now is the endless applications of AI in payments from taking on Fraud, AML, to cross selling based on behavior, to helping Small Businesses with invoicing, cash management, to automated underwriting………….

So for all these areas to transform teams need to drive the AI in payments and the market need has to be recognized. I believe that both Payment leaders and start ups are starting to realize the opportunity – let’s see where the road takes the Payment industry!

How Artificial Intelligence is impacting Frictionless Payments

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As technology continues to evolve it’s an exceptional time to be part of the payments industry where areas of artificial intelligence are continuing to make digital payments and money movement faster and easier for businesses and consumers.

Artificial intelligence is helping to deliver personalized banking experiences in a number of ways.

Machine vision is storing facial recognition data to enable payments go through today. Biometrics is a business a usual method to access or initiate payments through the smartphone. Voice activated payments through AI powered virtual assistants is another innovative area that will help continue to support the growth of digital commerce.

AI continues to help uncover fraud, AML and support Risk in money movement. Machine learning is helping payment and financial institutions with KYC (know your customer) by enabling a 360 view of the customer though data from a variety of sources both online and offline. The beauty of leveraging AI technologies such as machine learning is that the programs learn from use cases over time so your programs will “ get smarter”.

Who cannot be excited about continuous improvement …..:0

Artificial Intelligence will Transform Business

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We are just starting to embrace the new frontier as Artificial Intelligence has gained momentum in so many different verticals. Its incredible the applications that are starting to be shared – machine learning models in sports, financial services, entertainment, the health industry . Natural Language Processing in Customer service and Social Media; Robotics in Manufacturing. Now is the time to embark on the AI journey to change the way your company does business. Computing is faster than ever, Algorithmns are more sophisticated and the Depth of Data seems endless. This is an exciting time as Technology is being Integrated into just about every industry that affects a consumer’s life- Financial Services, Automobiles, Retail, Healthcare etc…

Donna Bailey is the Innovative Leader you want to include on your Strategy or Product Marketing team to embark on the new milestone of Fin Tech, Auto Tech etc. I AM ALWAYS FORWARD THINKING – Strategic in my approach, Results oriented, Collaborative and Customer Focused. Passionate about data – Machine Learning and Artificial Intelligence are reasons to roll my sleeves up and look at the value these data sets bring to the business. I am ready for a new chapter in my career ! Are you looking to drive revenue and profitability for your product or division?

Donna Bailey should be leading that initiative as part of your organization . I have fundamentally grown the profitability for American Express, Symantec,Visa and Wells Fargo . I have delivered sales, new revenue and customer engagement for millions of consumers. Customers are the Lifeblood of Business (new and existing) . Seamless Customer Experience on the most Relevant Device is the only way to continue to grow Strategy and Customer Insight. Data and Analytics are key ingredients;Channel performance and optimization are critical. Creativity and Timing (Brand Positioning , Relevant message, Right time) helps to insure performance. I am a PASSIONATE Leader who DELIVERS.

Professional Summary

Innovator with expertise in Delivering Result Driven Customer Programs that drive incremental revenue. Strategically Changed the Business for American Express, Symantec,Visa and Wells Fargo through Effective Marketing Strategies. Managed multimillion-dollar global product and service launches through strategic planning and effective collaboration. Effective Leader of Product Marketing teams in Fortune 50 and Fortune 500 companies. Built a multi million-dollar program for American Express called Membership Rewards Online Specials . Launch Mobile Offers Program on behalf of Visa before rest of the Offer industry. Brought Wells Fargo Credit Customers into Mobile marketing . Ecommerce/Mobile Marketing Leader Payment Expert changed the Landscape Product/Program Marketing Management Acquisition/Retention Marketing Strategic Planning and Analysis Customer Segmentation and Target Marketing Direct Marketing and Merchandising Channel Management and Optimization Research and Customer Experience Campaign Implementation