Human Vs Machine: What Does AI Mean For Marketers Today
Will digital marketers become obsolete? How AI will affect marketing and how businesses can prepare for greater automation.
The relationship between man and machine has changed significantly in recent years. This relationship has transformed marketing too: from the initial digitization, to the introduction of social media, to increasing automation thanks to AI and Machine Learning technologies. In the current digital climate, technology has been widely recognized as the enabler of economic growth and fast-paced innovation for companies, allowing us to scale processes and manage high volumes of data for marketing.
The growing involvement of ‘machines’ in the field means a change in profile for today’s digital marketer. Despite that, there’s still a central necessity for human creativity and intuition, meaning there isn’t an immediate danger of digital marketers becoming obsolete. Nevertheless, when approaching the introduction of new technologies, it’s crucial not to overlook organizational elements and the human level in order to ensure effective implementation and employee satisfaction. Those companies that have moved fast to innovate the entire customer journey by leveraging latest technological advances, whilst also keeping the human level in mind, will be those that win the race for digital mastery.
Human Vs Machine: The relationship over time
A crucial point in the ever-changing relationship between human and machine was in 1997, when chess master Gary Kasparov was beaten at chess by IBM’s Deep Blue machine. It was at this moment that people began to consider the possibility that the capabilities of computers would develop such that they would render humans obsolete at some point. This created panic, with people wondering whether, in fact, they should just give up.
However, in fact, ever since computer software has become more accessible, chess masters started to leverage this technology in order to improve their chess performance and become as good as the computers capable of beating them. Kasparov in fact said that the computer’s performance enabled him to be more strategic via the extensive use of computers to practice, whilst still leaving an important space for a human touch:
“The computer could project the consequences of each move we considered, pointing out possible outcomes and countermoves we might otherwise have missed. With that taken care of for us, we could concentrate on strategic planning instead of spending so much time on calculations. Human creativity was even more paramount under these conditions.”
How does this impact on today’s digital marketer?
Though this might seem entirely unrelated to the world of digital marketing, in fact there are key similarities between the two disciplines. Both are highly quantifiable pursuits with clear outcomes which have historically relied solely on human intuition and creativity for success. They also both rely upon a continuous reassessment of the ‘board’ (in the case of marketing, customer behaviors and history) in order to decide upon the next move (or campaign or communication). Indeed, just as Kasparov spoke of the enduring importance of human creativity, digital marketing still relies on a key lynchpin: human intuition that comes with experience.
Today’s digital marketer still has an intuitive understanding of their audience’s makeup and preferences. They still operate in a world where humans make the decisions, and computers provide the numbers to support their decision-making. Digital marketing today still awards importance to measuring campaign outcomes and audience response (for instance, in techniques such as control groups and attribution analysis which require human emotional responses). That said, digital transformations and the introduction of AI and Machine learning will have profound effects on key tools used by digital marketers in the Adobe Experience Cloud. Indeed, each and every solution in the Adobe Experience Cloud will be affected by these changes, and marketers will need to be aware of the potential disruptions, and benefits to be gained from automating some currently manual tasks.
How AI impacts the Adobe Experience Cloud
The central prerequisites to leverage AI are:
- A solid data foundation.
- Risk assessments and availability. This particularly applies to Swiss and German markets. Data from a backend or a CRM for instance, will need to be risk assessed and approved for application in machine learning or AI projects.
- Data strategy. This is needed for every product, website or app, ideally with a standardized data layer throughout the entire company that collects data, in order to make it available for services like machine learning.
AI will have a profound effect on many areas of the Adobe Experience Cloud, though it’s still currently in its early stages of development. To examine these effects further, we’ll take a look at two particular areas which are set to be radically altered by the introduction of this technology: Adobe Analytics and Audience management.
What will be the impact of AI on Adobe Analytics?
The process of deep-diving into data to produce analysis and reports is a highly time-consuming process. This process necessitates a knowledge of which variable creates what, in order to generate data that’s actually useful to marketers. This means there’s plenty of room for automation to take over, though it still remains a thing of the future.
There’s potential for automation in the following areas in particular, which tend to be both very useful features that directly support marketers, as well as highly time-consuming when carried out manually:
- Anomaly Detection
- Identification of Patterns
- Alerts and Notifications
- Human Voice Interface
What will be the impact of AI on Audience Manager?
Audience manager sits directly on Adobe data, creating segments based on that data for personalization. This too is a very time-consuming tool to operate. Whilst with Analytics there tends to exist a functioning operating model and analytics to manage reports and dashboards, the recent introduction of audience manager means it can often be managed by just one person in an entire organization. Currently, the creation of traits and segments in Audience manager has to be done manually. To clarify, traits refer to a characteristic of a segment, such as a classification of users that own Apple products. The evaluation of the performance of these segments and the resultant personalization is another task that is currently undertaken manually, demanding a great deal of time and personal judgment. In addition, an area that’s fertile for AI which is currently a granular, human process is the management of data sources (such as a CRM) and destinations (where it’s shared for personalization, like Twitter, Google Adwords or your website).
Therefore, there’s strong potential for assistance from AI in the following areas of Audience Manager:
- Automated Trait and Segment Creation
- Segment Performance Analysis
- Attribution and Scoring
Human vs Machine: The Organizational Level
As we consider the evolution of human vs machine relationship in the years to come, it appears routine tasks will be carried out by AI in the near future. This means machine can essentially handle repetitive granular tasks in order to create space for creative work on the part of individuals. This means, for now at least, that humans won’t be replaced entirely by machines. Experts agree that a general AI that trains itself on completely new fields, for instance an AI built for a car training itself to operate another process entirely, is decades away still. That said, job profiles are certainly set to change, presenting a key area for consideration. Clearly there are technological changes afoot, but the necessary human and organizational changes mustn’t be overlooked either.
Implementing automation and AI when restricted by company siloes will prove ineffective and difficult. A business infrastructure in which HR, finance, customer service and tech only focus on their own specific projects, without a general awareness of the common objectives and wider strategy regarding investment in innovative technology, will not integrate these innovations in a productive way. This will eventually result in an inconsistent and poor customer journey for end users. Therefore, when undertaking digital transformation, in particular towards automation of previously manual tasks, it’s important to be aware of the scope of influence of these changes, which could affect:
- Performance management
- Skills and talent
In fact, these types of transformations will impact everyone and everything. To go digital you not only need to make technological amendments, but you need to be agile, autonomous and work well in a team. When AI substitutes human tasks, it’s often difficult for teams to feel empowered as agents of change, since they can feel as though their individual contributions are no longer valid. Therefore, when we talk about digitalization processes, we often speak about technology as a lynchpin. However the true anchor and facilitating factor when managing human vs. machine transitions and issues is the organization of the human level.
Managing the human: Getting ready for the change
In order to successfully navigate this ever-evolving relationship between human and machine, teams and technology, companies must address the organizational challenge to examine how they can self-correct and self-cure. This will involve a number of steps:
- Look at others who are further ahead in the journey and have successfully digitized
- Partner effectively to plug skill gaps in order that you can learn new skills on the way
- Build the right skill development plans
- Move towards team-based performance management
- Start with a pilot and scale gradually: don’t start at 100%
The relationship between humans and machines is one that has changed radically in recent years, and will continue to change rapidly in years to come. We find ourselves at a crucial moment at which technology has been widely recognized as the enabler of economic growth and fast-paced innovation, allowing us to scale processes and manage high volumes of data.
However, this doesn’t mean today’s digital marketers will be made obsolete: rather there’s still substantial need for human creativity, intuition and instinct born from experience alongside automated processes. That said, we should be aware of specific impacts of technology such as AI, which will change every element of the Adobe Experience cloud, in particular in regard to analytics and audience manager.
Finally, when approaching the introduction of new technologies such as these, it’s crucial not to overlook organizational elements and the human level in order to ensure effective implementation and employee satisfaction. The human/machine relationship is set to change the landscape of digital marketing, and indeed our world in general. It’s by addressing organizational challenges, and understanding particular technological impacts, that businesses can truly leverage the power of AI and Machine learning to ensure competitivity in the years to come.