Prior to the resurgence of AI and its eventual commercial application, executives have had to rely on inconsistent and incomplete data. Today’s AI systems start from zero and feed on a regular diet of big data. This eventually provides executives with sophisticated models as the basis for their decision-making.

According to PwC’s Rao, limitless outcome modeling is one breakthrough in today’s AI systems. He reiterates: “There’s an immense opportunity to use AI in all kinds of decision making”.

In marketing, AI is used to bridging the gap between analytics and how strategies are used and executed. AI marketing uses artificial intelligence technologies to make automated decisions based on data collection, data analysis, and additional observations of audience or economic trends that may affect marketing efforts.

AI in Management Decision Making

A refined class of Artificial Intelligence techniques is revolutionizing the support of decision making, especially under uncertain conditions by such means as coordinating data delivery, analyzing data trends, providing forecasts, developing data consistency, quantifying uncertainty, expecting the user’s data needs, providing information to the user in the most appropriate forms, and suggesting courses of action.

Nowadays, decision-makers and business executives have reliable data analyses, recommendations, and follow-ups through artificial intelligence systems to make better choices for businesses and employees. Not only does AI enhances the work of individual team members but also improves the competitive standing of the business.

According to McKinsey Global Institute’s research, AI could deliver an additional output of $13 trillion to the world economy by 2030, which would boost global GDP by nearly 1.2 percent a year. Acting as a capital-hybrid, AI can aid the growth of both the economy and humans. This will definitely have a revolutionary impact on the decision-making process.

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Scope of Application of AI in the Marketing Industry

AI can be helpful to companies that can change the technique in which these companies engage with customers, innovate & communicate their processes, and test the sales process. AI uses techniques such as natural language processing, machine learning, adaptive learning, deep learning, and computer vision to analyze enterprise data and provide detailed insights that help in making informed decisions for enhanced management of the enterprise.

Predictive analytics offered by artificial intelligence help marketing enterprises in customer acquisition and lead generation. Using AI, marketers can also benefit from advertising optimization techniques such as media content, placement, and advertisement and campaign optimization based on usage patterns and customer behavior. With the use of AI-based virtual help such as digital assistance, chatbots, and recommendation engines, marketing enterprises can manage customer relationships better, and help in understanding customer’s preferences which improves the overall experience. It projects a growing demand for digital assistance to drive the growth of AI in marketing.

Some major players active in the development of Artificial Intelligence (AI) in the Marketing Market include IBM Corporation, Google Inc., Salesforce.com, Inc., Albert Technologies, Amazon, Intel Corporation, Microsoft Corporation, NVIDIA Corporation, and Sentient Technologies Holdings Ltd.

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The evolution of marketing analytics towards AI

The business being dynamic is strengthening day by day, we can see such innovations in every sphere of the business. The marketing sphere has also not left untouched of it, with the change in the communications mode and integration, conventional marketing has been growing into non-conventional marketing through the inculcation of Artificial Intelligence. The development of this had led to a major change in marketing to study the evolution of AI in marketing. The adoption and the perspective of the customers toward AI marketing have been desired to study through the medium of this research. The study has concluded that although there has been major inclement toward AI still its proper implementation would take some time.

Data Protection

When discussing artificial intelligence (AI) it’s hard not to talk about the Data Protection regulation at the same time. One challenge of big data analytics is to maximize utility whilst protecting human rights and preserving meaningful human control.

Marketing involves data that gives insight into a customer or lead demographics, brand interactions, and buying behavior and high-quality data is vital for AI. Feed AI software good information to give the algorithms the best chance of making excellent decisions and accurate analysis.

This also means a higher level of customer trust as it forces companies to be more transparent with their audience about how they use data, and customers experience less reluctance to hand over personal data as they know their privacy is a top priority.

B2B Marketing

One major factor that determines how successful you will be as a B2B marketer is your ability to maintain a consistent customer base. Modern AI can scour for potential customers using relative set-points enabling you to focus on what is important and who is important to your business. Technologies like this will save the sales and marketing teams' countless hours, along with precious company resources. AI has the potential to transform B2B marketing by predicting consumer behavior, by relying on consumer data and historical actions. If used, a B2B marketer would have the advantage of tailoring products and services to fit in the customer's changing needs in real-time. Content creation is an aspect of AI that has not been sufficiently developed. However, several innovative technologies along these lines have emerged in recent years. With tools like these becoming more and more accessible, the prospect of having a robot as a content writer.

Public Sector Marketing

The Artificial Intelligence market is constantly developing and presents great opportunities for private investments, but it must also be the object of interest by public entities, both from the point of view of investment and at the level of regulation. Most times, AI can provide support services with a high customization component. This personalization represents a truly fundamental change in relations between the administration and the citizens. Using these instruments shall be associated with the satisfaction of certain social challenges. The roadmap must go through experimentation and then scale the systems

While public sector authorities are progressively aware of the transformational effect of information and AI-fueled solutions, the data required for AI solutions to be created and deployed is regularly neither available nor discoverable. The public sector has various regions that could profit from AI. There are various citizen-facing roles, like health and social services, justice and policing, border services, revenue, administration and pensions, and social security, where artificial intelligence can support the public sector.

AI in Strategic Management

Leveraging the use of AI systems in strategic management places requirements on both the appropriate organizational infrastructure and the working methods of management teams. Research shows that the organizational culture and the process of how AI is applied are decisive for organizational success.

Military Experience

Around the world, AI is already seen as the next big military advantage. Early this year, the US announced a grand strategy for harnessing artificial intelligence in many areas of the military, including intelligence analysis, decision-making, vehicle autonomy, logistics, and weaponry. The Department of Defense proposed a $718 billion budget for 2020 allocates $927 million for AI and machine learning. Existing projects include the rather mundane (testing whether AI can predict when tanks and trucks need maintenance) as well as things on the leading edge of weapons technology (swarms of drones). But as the Tesla hack shows, an enemy that knows how an AI algorithm works could render it useless or even turn it against its owners. The secret to winning the AI wars might rest not in making the most impressive weapons but in mastering the disquieting treachery of the software.

Cognitive bias

Thinking errors, known in Psychology as Cognitive Biases, can be qualified into different types and are inherent to the human condition. It is important to consider cognitive biases when planning the next steps of the business. Even when the algorithms are perfect and the outputs are immutable, our cognitive biases make our interpretation of data unreliable at best. Everyone has these biases to one degree or another which makes it concerning that there’s been so little research on how they affect data interpretation. Artificial intelligence learns logic built through algorithms as fundamental stepping stones that evolve in stature as time progress.

Planning processes

Process Planning is an important activity in an intelligent manufacturing environment. Several techniques have been proposed, implemented, and tested. Modern artificial intelligence planners are reasoning systems that use expressive declarative languages for representing knowledge about goals, and actions for achieving them, along with their preconditions and effects. Thus, these planners are capable of finding solutions chaining action sequences to achieve goals or preconditions of other actions. Because of the declarative nature of the languages, they are more flexible than logic rule-based systems in that not every combination of elements must be explicitly represented, but only the system’s capabilities. Thus, these systems allow for easy extension and implementation, because they are more general than special-purpose systems.

Benefits of AI in Marketing Decision Making

AI includes the automation of cognitive and physical tasks. The benefits of applying AI to strategic marketing decision-making are expected to include these:

  • It helps people perform tasks faster and better and make better decisions.
  • It enables the automation of decision making without human intervention.
  • AI can enhance automation thus reducing intensive human labor and tedious tasks.
  • Artificial intelligence enables businesses to process a bulk of data in real-time. Through this, AI provides meaningful insights that can solve recurring business issues.
  • Using explorative and predictive data analysis, businesses can minimize risks and maximize effectiveness. With this, businesses can not only capitalize on short-term opportunities but also boost profits and revenues in the long-run.
  • Executives can identify patterns that may not be very clear to human analysis.

Example:

A lot of times the complexities involved in marketing decisions create a hindrance in making accurate predictions. Complexities include a good understanding of the customer wants and needs and the ways to align products with these requirements. Businesses must know what their customers want and then design the products accordingly. Similarly, they can make good short and long-run marketing decisions with some insights on changing consumer behavior.

AI modeling and simulation techniques use valuable insights into buyer personas. Implementing these methods into the decision-making process helps organizations to improve brand loyalty by predicting consumer behavior. AI systems can help real-time decision making through a decision support system which also assists in forecasting, data mining, and useful analysis of the recent trends.

Progress to Date

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The beginnings of modern AI can be traced to classical philosophers' attempts to describe human thinking as a symbolic system. To allow comparison with human performance, artificial intelligence can be evaluated on constrained and well-defined problems. When the field emerged at the end of the 20th century it was hoped that computers would be able to operate on their own, with human-like abilities - a capability known as generalized AI.

Today, we live in the age of big data, in which we have the capacity to collect huge sums of information too difficult for a person to process. Artificial Intelligence in this regard has been quite fruitful in several industries such as technology, banking, marketing, and entertainment. If algorithms don’t improve much, big data and massive computing simply allow artificial intelligence to learn through brute force.

Future of AI in the Marketing Industry

AI marketing has enthralled marketing teams all over the world. According to a study from Statista, 84% of respondents said that AI gave them a business advantage over competitors.

Below, we review the potential influence of AI in marketing in the upcoming years, which include:

Improved product and content recommendations

Many blue-chip tech companies have built their product offering and business models around the concept of targeting customers with highly relevant and customized products or services. All of this is the result of AI-based clustering and data interpretation compounded with demographics and profile information. By continually pairing and adapting to customer likes and dislikes, companies are now able to put forward new and tailored recommendations in real-time.

Better social engagement and customer service

The quality of social engagement and customer service before, during, and after the sales process is important. AI-powered intelligent messaging platforms are helping businesses improve their overall customer service engagement experience.

Whether it’s retail, e-commerce, or healthcare, these platforms can register customer suggestions and feedback based on their buying habits. And this is where the future of customer service lies.

Improved search engines

AI has profoundly impacted the way we search for information online, along with the overall quality of the search experience. With innovations like semantic search and natural language processing (NLP), search engines are able to crawl through multiple websites, correlate similar links, auto-correct mistakes, and find relevant search results.

Equipped with these technologies, customers can discover products well-suited to their needs and interests, even if they weren’t originally sure what they were looking for.

Better ads

With these advancements in big data and the proliferation of social media platforms, marketers are already working overtime to create smarter and more effective ads. Using AI-based solutions, marketing teams dig deep into social profiles and keyword searches. Markets can ultimately create human-level outcomes using this information gathered by AI.

These are only a few aspects of marketing that AI has the potential to improve.

Conclusion

We need to grow further and bring AI into the workflow as a primary processor of data. For routine decisions that only rely on structured data, we’re better off delegating decisions to AI. AI is less prone to human cognitive biases. We can train AI to find segments in the population that best explain variance at fine-grain levels, even if they are unintuitive to our human perceptions. AI has no problem dealing with thousands or even millions of groupings. And AI is more than comfortable working with nonlinear relationships, be they exponential, power laws, geometric series, binomial distributions, or otherwise.

AI is infiltrating every aspect of our daily lives. There’s no better time for marketing teams to start leveraging AI strategies to create personalized experiences for their customers.

With the expected growth of AI across all segments and industries, the least any marketer can do is dedicate time and resources to AI solutions. In doing so, they’ll ensure that their marketing strategy is poised for continued success, both now and in the future.