Elon Musk Ventures into The AI Frontier With xAI
Billionaire entrepreneur, Elon Musk, has entered the AI market with the launch of his much-awaited artificial intelligence start-up, ‘xAI’. Musk took to Twitter to announce that the formation of the said start-up was to “understand reality.” As per xAI’s website, their goal is to understand the “true nature of the universe.”
Announcing formation of @xAI to understand reality
— Elon Musk (@elonmusk) July 12, 2023
Musk, who is currently heading X Corp, Tesla, SpaceX, Neuralink, and Twitter, will also lead xAI. However, xAI will be separate from X Corp, but work closely with X (Twitter), Tesla, and other companies to “make progress towards the mission.” The team consists of experienced specialists from DeepMind, OpenAI, Google Research, Microsoft Research, Tesla, and the University of Toronto. Dan Hendrycks, Director of the Center for AI Safety will serve as the advisor for the xAI team.
Elon Musk has previously served as the co-founder of OpenAI, the company that launched ChatGPT but stepped down from its board in 2018. This led to a lot of prompts stating that Musk wanted to launch his own alternative to the chatbot. He further criticized OpenAI’s chatbot, ChatGPT, claiming that it embraced left-wing biases. He had also stated that he would be soon working on launching an AI which would be called “TruthGPT” to rival Google’s BARD and Microsoft’s Bing AI.
Musk, along with 1,000 other prominent leaders had signed an open letter to halt the development of advanced AI systems stating the extreme threats that society and humanity would face. He, on several occasions, has emphasized the need to regulate the AI sector as it has the potential to destroy civilization.
In a Twitter Spaces discussion, he had mentioned that xAI was going to be “pro-humanity from the standpoint that humanity is just much more interesting than not-humanity.” With xAI, Musk plans to build a safer AI.
With the launch of xAI, Elon Musk has pioneered a new path toward better understanding the reality of AI developments. He has positioned himself as a forerunner in introducing moral frameworks in order to steer the industry.
In order to get more insights about the company, xAI has arranged for a Twitter Spaces chat on Friday, July 14th, where you can meet and ask questions to the panel.
Read more: Battle of the Ads: Borzo Reveals Who Wins – Advertising Team or AI?
Google and Omnicom Collaborate to Enhance Advertising with Generative AI
Omnicom has partnered with Google to integrate the search giant’s generative AI models into its ad tech platform. This collaboration marks the first commercial application of Google’s generative AI technology, which was previously not widely available. Through this integration, brands will gain access to generative text and image capabilities, enabling them to create dynamic and engaging content. This innovative partnership aims to enhance the creative capabilities of Omnicom’s ad tech platform and provide brands with new opportunities for personalized and impactful advertising.
Omnicom will leverage the capabilities of Google Cloud’s Vertex AI, specifically its foundation models such as PaLM 2 and Imagen. PaLM 2 is Google’s large language model for text and Imagen is similar to DALL-E, for generating images.Imagen allows organizations to generate and customize studio-grade images at scale from input text with low latency and enterprise-grade data governance.
Through seamless integration into their open marketing orchestration platform Omni, agencies and client teams will now have unprecedented access to these powerful models. This integration will enable expediting the content development process, providing enhanced efficiency and creativity.
Jonathan Nelson, CEO, Omnicom Digital said,
We’re thrilled to have another first-mover advantage with Google Cloud’s foundation models and to continue strengthening the use of Generative AI within Omnicom.
By creating Omni as an open operating system, we’re able to quickly integrate these innovative models and mobilize them to thousands of Omnicom employees that use Omni. We’re especially excited to see how Imagen will unlock greater inspiration for our people and elevate the ideas created for clients.
As reported by Adage, Nelson further mentioned that they are closely looking at the video. The models developed by Google were trained using “copyright-free” data. The issue of copyright has hindered the broader adoption of certain AI applications in marketing as agencies and brands have concerns about utilizing the material for which they don’t possess proper licensing.
Nelson said,
Their version of Imagen is particularly interesting because it’s copyright-free which is a huge deal for us so it can be applicable to advertising.
June Yang, Vice President of Cloud AI and Industry Solutions at Google Cloud,
Our partnership with Omnicom deepens this commitment as it allows marketers to create studio-grade images with mask-free editing for any business need, in a platform where they are already familiar, with only a few typing prompts. We cannot wait to see what they create!
Adage reported Omnicom will train machines using data from brands’ entire marketing copy archives to develop custom AI models. Nelson introduced the concept of “data stacking,” where the agency combines its own data with clients’ data, specifically benefiting media and optimization. This approach enables the creation of proprietary products based on the developed models.
This partnership is the latest collaboration between Google and Omnicom, who have closely collaborated together for decades. This includes their early collaboration as an alpha partner for clean room integrations with Ads Data Hub.
Interesting Read: Microsoft Store Ads Expand to Bing Search Results, Empowering Global Advertisers
The AI Search War: Microsoft & Google Compete for Search Engine Leadership
The swift ascent of ChatGPT, developed by OpenAI and supported by Microsoft, has caused a sensation worldwide with its capability to deliver rapid results. In fact, within just two months of its release, the app has garnered 100 million users, making it one of the quickest-growing applications globally.
Microsoft announced the launch of its latest AI product, a revised version of Bing-powered by a custom-made OpenAI language model that is designed specifically for search and is more powerful than ChatGPT. The tech company describes tools as an AI copilot for the web. The company will also be upgrading its Edge browser, bringing new features to the table.
The announcement from Microsoft arrives around the same time as Google’s announcement of Bard, its answer to ChatGPT. As ChatGPT posed a challenge to Google, the company responded with Bard. Microsoft has now entered the field with a cutting-edge search engine that utilizes artificial intelligence.
Interesting Read: Google’s BARD vs ChatGPT: Which AI Will Rule the Search Realm?
However, during its live demo, Google’s AI algorithm, Bard, made grotesque errors, resulting in a loss of $100 billion in market capitalization for its parent company. What precisely occurred to cause such significant damage to Google? Industry specialists have pointed to a mistake in the response given by the chatbot in Bard’s promotional material. This error happened in response to the query, “What new discoveries from the James Webb Space Telescope (JWST) can I tell my nine-year-old about?”
Bard’s response in the online demo includes an answer that states the telescope “took the very first pictures of a planet outside of our own solar system.”
The error was picked up by many astronomers including Grant Tremblay, an astrophysicist at the US Center for Astrophysics, who tweeted:
Not to be a ~well, actually~ jerk, and I'm sure Bard will be impressive, but for the record: JWST did not take "the very first image of a planet outside our solar system".
the first image was instead done by Chauvin et al. (2004) with the VLT/NACO using adaptive optics. https://t.co/bSBb5TOeUW pic.twitter.com/KnrZ1SSz7h
— Grant Tremblay (@astrogrant) February 7, 2023
The incident highlights the fierce competition between Google and Microsoft, as Bard was developed to rival Microsoft-backed ChatGPT. In less than a week, we witnessed the two big tech giants engage in all sorts of acrobatics to secure their positions and control the market as they compete to lead the next wave of AI-enhanced computing.
Who will win the AI-powered search/chat war?
Despite the fact that the market is still bullish on Google, experts believe they are still a few steps behind Microsoft, which has recently caught up to ChatGPT’s advances. Today, Microsoft stands ahead on the AI front. People are curious about the potential impact of large language models (LLMs) on search. Last week, Microsoft caused a sensation by integrating OpenAI’s technology into Bing search.
“First of all I have the greatest of admirations for Google and what they’ve done. They’re unbelievable with great talent. I have a lot of respect for Sundar Pichai and his team.I just want us to innovate. Today was the day when we brought some more competition to search. We’ve been at it, believe me, I’ve been at it for twenty years and I’ve been waiting for it.
But at the end of the day, they are the 800 pound gorilla on this which is what they are and I hope that with our innovation they will definitely want to come out and show that they can dance and I want people to know that we made them dance and I think that will be a great day.”
– Satya Nadella
Google’s recent actions certainly make it look like they are dancing. Despite their superior AI models and expertise, they have not effectively commercialized this technology due to a lack of a culture that supports innovation. However, the pressure from Microsoft and OpenAI is quickly transforming this situation.
The intense competition between the leading tech companies has been captivating to observe, with each company making impressive announcements in quick succession. Behind the scenes, there is a fierce battle being waged in the boardrooms of these tech giants. The heightened interest in the latest AI-powered version of Bing has resulted in high demand for the product, causing a waitlist to form for those eager to try it out.
Race to ace the AI-powered search industry
Google holds a dominant position in the global search market with a market share of over 93%, while Bing’s share is 3% in January, 2023. According to Microsoft Chief Financial Officer, Amy Hood, search advertising represents a significant portion of the digital advertising industry, accounting for an estimated 40% or $200 billion of the $500 billion market. The majority of these revenues are generated by Alphabet, which reported a total of $163 billion in search advertising last year.
Its business model revolves around advertising and search-based revenue, with roughly 60% of its income coming from Google Search. Microsoft announced the integration of ChatGPT into Bing sent Google into a state of emergency. A significant disruption to this income stream could have disastrous effects. The emergence of ChatGPT as an AI-powered alternative to search represents a potential threat to Google’s business.
Microsoft may be counting on its chatbot-powered information search to attract new users who could then use Bing for higher-value searches. This strategy may come at the cost of lower margins, at least until expenses can be reduced. However, it would only be justified if Microsoft can effectively challenge Google and gain a significant market share.
“for every 1 point of share gain in the search advertising market, it’s a $2 billion revenue opportunity for our advertising business.”
-Microsoft
Challenges for Google: Balancing Cost and Market Dominance
The shift to AI-based large-language models could also increase Google’s costs, in addition to the threat to its market share. A research note from Morgan Stanley analyst Brian Nowak, quoted by Barron’s, highlights the potential for increased costs for Google due to the shift towards AI-powered search queries. The note indicates that a 10% shift in queries to AI will result in a $1.2 billion increase in Google’s operating costs. If the shift were to reach 50%, expenses would grow by $6 billion and trim pretax profits by 6%. Nowak’s perspective is that AI-powered search queries will cost Alphabet roughly five times more than the current method.
The partnership between Microsoft and OpenAI presents a double challenge for Alphabet investors, as it could result in a loss of market share and increased costs. This comes at a time when Alphabet is already facing regulatory scrutiny over allegations of monopolistic practices and misinformation on its platforms. The Microsoft-OpenAI deal has the potential to add additional stress to the already challenging situation for Alphabet and its investors.
The current technology and business model that has produced consistent profits for 20 years may be challenging to let go of. However, CEO Sundar Pichai is determined to resolve this “innovator’s dilemma” and find the best solution. On the other hand, Microsoft CEO Satya Nadella is hoping that Bing will gain popularity as a search term before Pichai finds a solution.
Wrapping up
In light of the recent “Bard AI fiasco,” Alphabet CEO Sundar Pichai must swiftly resolve the “innovator’s dilemma” and find a suitable solution. Meanwhile, Microsoft CEO Satya Nadella has high hopes for Bing to establish itself as a popular search term before Pichai’s resolution. The pressure is on both tech leaders as they navigate the constantly evolving technology landscape and competition in the search engine market.
Microsoft is ready to reclaim its position at the forefront. Google, be prepared, as Microsoft takes the lead in this first round. Witnessing this AI search engine battle is going to be a lot of fun!
Interesting Read: Tête-à-Tête With ChatGPT- The Power Of AI
Nabd launches Personalized Email Newsletters Powered By AI and ML Algorithms
Nabd, a leading personalized Arabic Content platform launched a new Personalized Email Newsletter product. It will provide opted-in subscribers a daily news digest tailored to their interests, autonomously curated via sophisticated AI and machine-learning algorithms. Content will be delivered to them by email – one of the most effective distribution methods available today.
Interesting Read: How Will Dubai’s Metaverse Sector Contribute To Its Economy By 2030?
Strong subscriber base
Nabd reaches over 25 million users, generating over 2 billion page views every month, making it the biggest Arabic app globally. The Daily Email Newsletter has already been opted in by over 5 million subscribers during the beta and alpha phases. Aso, Nabd’s digital properties such as its mobile apps and web portal attract thousands of new subscribers every day.

Image Credit: Zawya
How do the AI and MI Algorithms work?
Advanced AI and machine-learning algorithms analyze massive volumes of content in real time, including news articles and videos. Afterward, based on geolocation, interests, past engagement, and consumption patterns, the feature curates the most relevant and trending stories for each individual user.
And That’s What They Said
Mr. Al’a Abukhalaf, VP of Business Development at Nabd commented,
Nabd’s Daily Email Newsletters is one of the powerful tools our partners can leverage to promote and elevate their brand, as it offers an exclusive cutting-edge opportunity for brands to sponsor the daily newsletter, staying top-of-mind across Nabd’s highly-engaged Arabic readers and capturing their attention at the most receptive mindset; while they seek and consume relevant and timely information.
Our opted-in subscribers will on the other hand enjoy a personalized, digestible news summary, playing an important role in increasing the reach and retention of the Nabd platform.
Interesting Read: 6 Data Privacy Trends To Look Out For In 2022!
IBM Adds Three New Ad Tools To Help Brands Grow Beyond Cookies
IBM announced three new ad tools to add to its growing suite of AI solutions for brands and publishers that don’t rely on cookies and trackers. The new capabilities are designed to allow brands to reach customers while maintaining their privacy.
The tech giant intends to work with industry leaders like Xandr/AT&T, Magnite, Nielsen, MediaMath, LiveRamp, and Beeswax to help accelerate the use of AI in the digital ecosystem. The IBM Watson Advertising suite of solutions leverages AI to help clients make informed, data-based decisions. It would expand the suite by adding a host of new capabilities. This includes ad attribution, video and over-the-top (OTT) creative, and audience prediction.
– Expansion for IBM Watson Advertising Accelerator: IBM is expanding its advertising accelerator that uses AI. It enables marketers to understand which creative content performs best, and now includes video and OTT platforms.
– IBM Watson Advertising Attribution: The company is launching a beta solution in the coming months. It will allow marketers to precisely quantify the efficiency of their advertising spend while understanding performance drivers.
– IBM Watson Advertising Predictive Audiences: This tool will help reach consumers that show similar behaviors.
The new AI-powered advertising products are an alternative to conventional cookies and trackers. Soon, Google will withdraw the support for such identifiers. Bob Lord, SVP, of Cognitive Applications, and Blockchain, IBM said,
While the advertising industry strives to re-emerge strong from the global economic and societal issues we faced this year, it’s also deep in the throes of a major transformation with changes to mobile identity, certain elimination of third-party cookies, compliance and regulatory shifts and increased demand for trust and transparency,
We believe AI will be the ‘backbone’ of the new era as the industry prepares for the next generation of advertising. Our work will be a step forward in our evolution to meet the advertising industry’s upheaval, and we are proud to help the advertising industry advance with the value of AI.
IBM is working towards a new ecosystem to accelerate AI adoption and in advertising that would bring together existing collaborators like Neilson and MediaMath as well as new partners like Xandr/AT&T and Magnite, with whom IBM is negotiating definitive agreements. The companies can help to reinstate trust and transparency in the marketplace with the next generation of IBM advertising technologies.
As quoted in Adweek, MediaMath CEO Joe Zawadzki said,
You think about sort of the conditions that led AI to become prevalent in finance, for example, like what needed to be true—the the idea that markets get big enough, that automation is available enough.
I think you’re seeing the same conditions for AI in advertising, where it’s gone from sort of experimental and on the side to mission critical for people to figure this out.
Read more: A One-stop Guide On All You Ever Need To Know About AdTech In 2020
A One-stop Guide On All You Ever Need To Know About AdTech In 2020
AdTech or Advertising Technology did around $800 Billion Worth Of Business In the US alone in 2019, making it one of the fastest-growing industries in the world.
Are you trying to understand ad tech? Just as advertising is the business of making advertisements, ad tech is the business of using technology to make advertisements faster, quicker, and efficient. The business is driven by powerful algorithms and data points. While it is not rocket science, but for the uninitiated, it can be challenging to understand what is ad tech and how its product and services work.
The ad tech industry fuels the global economy with big investments, employment, and ad spend. Digital advertising has reached new heights of complexity, with the rise of programmatic advertising, AI, and automated interactions between computer systems reducing human intervention. Today’s omnichannel ad campaigns reaching to different platforms all at once from publishers’ websites, mobile apps, social media to search engines. Campaigns using tailor-made and highly targeted ads to reach audiences. This process involves many participants- advertisers, publishers to third-party vendors. The technology used in advertising to store, manage, and deploy data is far more sophisticated.
This guide will give you a sneak-peek into the world of technological advertising and understand the growing ad tech industry. As you read further, you will understand the ever-changing ad tech ecosystem.
What is Ad Tech?
Ad Tech also is known as Advertising Technology covers a range of tools and software that can be helpful for brands and agencies to plan, strategize, and manage all digital advertising activities.
The AdTech ecosystem consists of two major entities – the advertiser (Demand-side) and the publisher(Supply-side).
On one hand, advertisers want to run effective campaigns and optimize their budgets to reach the target audience, gain customer insights, and measure ROI.
Whereas, on the other hand, publishers cater to the need of advertisers and generate revenue through ads by displaying ads on their publications like websites, apps, etc, increase ad impressions, bids for ad slots and visitor insights. These are significant factors that publishers need to consider to maintain the platform User Interface (UI).
Adtech helps advertisers and publishers achieve their goals in harmony by providing solutions that meet the demands of both parties. A few examples of AdTech platforms include Pubmatic, Adroll, MediaMath, SmartyAds, and many more.

Image Credit: MarTech Advisor
Programmatic Advertising Explained
After a brief understanding of ad tech, let’s step into the world of programmatic. You will come across concepts like programmatic advertising, Real-time bidding, and programmatic direct. Let’s discuss it:

Image Credit: Martech Advisor
- Programmatic Advertising Definition:
It is projected to be the game-changer for digital advertising. Programmatic automates the process of buying and selling online advertising space with the help of technology and data. This means, with the introduction of programmatic publishers, advertisers or agencies don’t have to sit across to discuss ad size, rates, et. Ad buying is done through algorithms and data insights.
- Programmatic Direct:
This a type of Programmatic digital advertising, where a publisher bypasses auction and reserves a portion or entire ad inventory for a particular buyer or advertiser at a fixed cost per mile. (CPM). Put simple, here the buyer and seller are known to each other and the ad placement is done programmatically.
- Real-Time Bidding (RTB):
Another type of programmatic digital advertising and also known as an open auction. RTB is when inventory prices are decided through an auction in real-time and open to both advertisers and publishers. This is the most feasible and preferable method of programmatic ad-buying because of scalability and flexibility.
The AdTech EcoSystem

Image Credit: Martech Advisor
The process of digital media buying is similar to the traditional media value chain except AdTech has multiple components in the ecosystem to keep the management of advertising campaigns easy for demand and supply-side platforms. Here are the key components of the AdTech supply chain:
1.Media agency: Responsible to allocate the advertiser’s expenditure budget across the channel. It is not involved in the creative aspect of ad campaigns.
2.Agency Trading Desk (ATD): Plans, buys, and manages ads across different platforms and is a set of services provided by the media agency.
3.Demand-side Platform (DSP): An essential platform for advertisers to buy, search, display video mobile ads. It enables advertisers to buy ad placements in real-time on the publisher websites made available by ad exchange and networks. Some of the DSP players are Simplifi, Smarty Ads, App Nexus, Double Click, and more.
4.Data Management Platform (DMP): DMP’s collect data from sources like websites, apps, social networks, campaigns, CRM’s, and more. Using AI and big data analytics to gather first and third-party data, advertisers, and marketers rely on them. DMP players are Lotame, Oracle Blue Kai, SAS data management and more
5.Ad Networks: The unsold inventory will be bought by ad networks from publishers and try to sell to advertisers using their technology. The popular programmatic advertising platforms for the ad networks are Taboola, Google Double Click Ad Exchange, Rocket Fuel, and more.
6.Ad Exchange: A dynamic platform to buy and sell ad impressions between advertisers and publishers without any intermediaries. Open X, App Nexus, Rubicon Project Exchange are examples of programmatic advertising platforms.
7.Supply Side Platform (SSP): The platform allows publishers to sell display, mobile ad impressions to potential buyers in real-time. Some of the key SSP players are MoPub, AerServ, App Nexus Publisher SSP, and more.
8.Ad Server: This platform is used by advertisers, publishers, ad networks, and ad agencies to run their campaigns. It determines which ad will be displayed on a website and also collect ad performances data such as clicks and impressions Double click for publishers, OPen X Ad server, Ad butler, and more are the examples.
Learn more: Programmatic Advertising Platforms in 2020: A Complete Guide
Is Programmatic advertising worth it?
The programmatic advertising statistics say it all. According to Zenith’s Programmatic Marketing Forecasts 2019, 69% of digital media will be programmatic in 2020.
- The total amount spent programmatically will exceed US$100bn for the first time in 2019, reaching US$106bn by the end of the year, and will rise to US$127bn in 2020 and US$147bn in 2021.
- 72% of digital media will be programmatic in 2021
- Ad spends growth is slowing down to 22% in 2019 due to industry challenges of privacy and supply-chain.
- Brands need to develop new targeting techniques using first-party data and customer data platforms in response to the ongoing death of the cookie.
Programmatic Display Advertising fastest-growing segment.
- The ascent of programmatic display advertising has been rapid. In 2012, only 10.4 % of global digital display spend was programmatic. However, it ballooned to 65.3% in 2019 and it is estimated that the share of programmatic display advertising will grow 69.2 5 and 72% in 2020 and 2021 respectively.
- How does it translate in dollars? In 2012, total digital ad spend was $37.8 billion and the programmatic display market was $3.9 million. Fast forward to today, digital display ad spend is $162.3 billion, out of which $106 billion is invested in programmatic display advertising. In 2021, global digital display ad spend is estimated to reach $204 billion, with $147.1 billion going to be programmatic share.

Image Credit: Marketing Charts
Programmatic marketing by country
One of the benefits of programmatic technology is it shows real-time data that helps companies take swift actions to adjust their strategy as per customer requirements. Digital marketers are considering buying programmatic media in-house due to its transparency. Programmatic has undergone massive growth in the following 6 countries out of which the UK and the US are the most advanced programmatic markets in the share of digital media.

Image Credit: Marketing Profs
As per eMarketer forecast, Programmatic ad spending will reach $59.45 billion in 2019, accounting for 84.9% of the US digital display ad market. It is estimated that 87.5%, or $81 billion, of all US digital display advertisements, will be bought via automated channels in 2021.

Image Credit: eMarketer
The above programmatic advertising statistics prove that the investment has increased Y-o-Y and marketers prefer programmatic advertising to buy digital display ads. Marketers are increasingly allocating their advertising budgets to digital advertising channels as it provides precise data that helps to reach customers effectively.
Learn more: 5 Programmatic Advertising Case Studies That Yielded Exponential Results
Artificial Intelligence can be leveraged in AdTech Industry
Artificial Intelligence(AI) and Machine Learning (ML) are two buzzwords in recent times. And why not, as it brings efficiency in whatever we do.
However, AdTech is a messy market now. Ironically, the good and bad part of AdTech is the abundance of data. True, we certainly have all the information to better understand the customers but most marketers aren’t aware of how to leverage the data and use it forward.
The way you advertise-is going to change extremely right before your eyes- thanks to Artificial Intelligence. Not all in the AdTech world have the analytical skills to evaluate the big data as not many are trained to use it and are misinterpreting them.
Adtech partnering with AI can help lower CPC prices, higher click-through rates (CTR), conversions, and better ROI. Let’s check out how AI can help the Adtech industry find better solutions in the following areas.
- AI in Ads Positioning
Developers don’t need to sit and determine which ad position will drive maximum revenue for the website. With the help of AI, employing machine learning algorithms study historical data to find relevant ads for the targeted user group.
Adtech has not used heatmaps previously but AI algorithms use them to learn where the visitors on the website are going and present them with the relevant ads. AI will help marketers to find the best ad positions by studying the maps in detail.
- AI in Ad Network Selection
There are many Ad Networks that provide different kinds of ads to websites owners and required to sort ads according to the websites. This is called Ad mediation and apt to earn high revenue for the websites.
By employing AI for ad optimization it reduces human effort by using a data-oriented approach that includes data, facts, and intelligence to make sure only relevant ads reach the end-user. Data will be user or website’s past history and facts will be website content, geo, and timing. Machine learning algorithms are employed to enhance the best ad-user match.
- Analytics
In the Adtech world, data analytics is not ‘taken seriously’ and publishers.are not happy about it. The AI-based approach will drive reporting and analytics to new levels.
Analytics will help publishers understand the content that drives the audience, placement of the CTA button to turn one time users into loyal users, and increase traffic. It will be a win-win situation for AdTech and parties- publishers, platforms, and users.
AI is the Future of Advertising
Today, digital advertising cannot exist without AI. Behind most online ads are the sophisticated delivery systems in place powered by AI. These systems place the ads before users, the coordination process happens in real-time and generally is automatic. It’s called programmatic advertising.’
According to eMarketer, 86.2% of all digital display ads will be bought via automated channels and nearly $19 billion in additional spending will enter programmatic display platforms between 2018-2020.
Also, 90% of mobile display ads are bought programmatically. On the other hand, AI also powers advertising products offered by Facebook and Google. In 2017, 90% of the new advertising business was captured by these firms.
In recent times, brands are under more pressure to deliver relevant, personalized, and contextual ads to individual customer preferences.
How AI makes Programmatic Advertising better
More companies are turning to AI for creating advertising relevance at scale.
For instance, if you want to advertise on Facebook,-an AI-powered algorithm determines the relevance of the score of your ad. This means that the score impacts the ad delivery directly and influenced by the experience of the ad delivery to Facebook users. Expect a low score if the ad is not liked or is irrelevant.
This decision is made by machine and is beyond your brand’s control independent of strategic or creative decisions
A marketing company like Phrasee launched an AI tool that writes Facebook and Instagram ads. The AI tool assesses a brand’s voice and copy, then the machine writes the ad that performs better than human-written ads. Recently, it helped reduce one client’s cost per lead by 31%. Another AI-powered tool is Albert that helps automate media buying, testing, and optimization. It enhances ad performance and delivers relevant ads to the right person. This shows that relevance at scale is possible in advertising.
Emerging Programmatic AdTech Trends 2020

Image Credit: MarketingToolbox
1. AI in Programmatic Advertising:
Technologies such as artificial intelligence(AI) and machine learning (ML)have involved programmatic ad buying or bid optimization. Programmatic campaigns are used by companies for more targeted net across platforms. By 2020, it is expected that there will be a shift towards automating technologies like AI and ML to get the most from data.
2. First Part Data Move Made Important by GDPR:
After the announcement of the General Data Protection Regulation (GDPR) in Europe, last year on cookie crumble or removal of third party cookies is gradually turning out to be beneficial. The regulations protecting the privacy of user data initially looked limiting to ad tech experts but is resulting in cleaner and more reliable data over time.
Learn more: Digital Advertising Industry Plans To Replace Cookies With First-Party Data
3. Digital Out Of Home (DOOH) and Mobile Location:
Digital DOOH combined with mobile location data has the potential to help marketers to drive conversions in the offline world. Integrated ‘home-to-out-of-home’ programmatic advertising approach provides a smooth experience to the customers.
4. Voice-activated Ads:
The adoption of voice-based to in-home smart devices has grown rapidly. Gartner predicted by 2020, 30% of web browsing sessions will be done through voice-first browsing. Amazon sold over 100 million Alexa-enabled devices in 2018 compared to 2017. A recent survey by VoiceBot.AI revealed 25% of respondents orders everyday household items through voice assistants followed by apparel and games and entertainment.
Programmatic advertising helps marketers to optimize these ad spaces across in-home smart devices, to on-app audio ad opportunities, and connect to consumers through in-store ads, ads in elevators and taxis, and more.
5. Wearables will enhance programmatic advertising:
Wearables collect data on location, lifestyle, health metrics, and more. The market penetration of smartwatches has grown multifold over the years and programmatic advertising is already making its way into this medium. For instance, it helps advertisers run banner promos to customers on their Samsung or Sony smartwatches. The wearable ecosystem has a huge potential to grow and programmatic adtech can bring greater opportunities.
6. 5G in programmatic advertising:
The high speed and no buffering will encourage the rise of more users to spend time on videos on mobile devices. It will enhance other technologies such as AR-enabled ad displays, VR without headsets, and innovative new digital outdoor mediums.
This will give programmatic advertising new opportunities to run more interactive ads without any lags across mediums. By 2024, the use of 5G in AdTech is predicted to grow to 1.4 billion.
7. Evolution of Personalization:
With Gen Z and Millennials- the biggest demographics -personalization is a priority as they like all things customized. Personalization in advertising is going to be inevitable as the choices of the new generation are different. Therefore, programmatic customization by advertisers is increasing offering personalized, relevant messaging to their target group.
8. Blockchains and Ads.xt:
Ad frauds are increasing over the past few years. A cybersecurity firm Cheq reports that ad fraud damages will touch $26 billion in 2020, $29 billion by 2021, and $32 billion the year after that.
The only way to handle the frauds is by bringing transparency in programmatic advertising. Blockchain and Ads.txt (an Interactive Advertising Bureau initiative – Authorized Digital Sellers) can help to remove unrequired middleman, domain spoofing, and verification of publishers and allow transactions using cryptocurrencies.
Learn More: Advertisers Look For Greater Transparency In Programmatic Ad Buying
9. Programmatic TV, podcasts and audio Ads set to grow:
The content on TV has changed drastically. There is a paradigm shift in TV viewing from cable TV to over-the-top(OTT) like Amazon Prime or Netflix via an internet connection.
Programmatic advertising has a larger role to play to ensure marketers get the best of both worlds. Programmatic TV is also going to get more important with its data-driven approach for buying and delivering ads.
Programmatic in podcasts and audio advertising is also growing. Apps like Spotify and Soundcloud are seeing more user acceptance and a new advertising landscape is being created for companies to monetize on.
10. Omnichannel Programmatic:
Forrester defines omnichannel marketing as ‘the practice of digitally sequencing advertising across channels, which is connected, relevant, and consistent with the customer’s stage in their life cycle.’ This is how programmatic advertising is going to be in 2020 and beyond.
A single marketing resource or an ad can be customized programmatically suiting various platforms through programmatic AdTech.
11. Agencies to work on outcome-based pay:
Discussions are making rounds to switch to an outcome-based remuneration model. With increasing ad frauds and agencies promise programmatic tech, advertisers fear how their budgets were used and where their ads placed. There was a lot of wastage in the space. Media buying companies started giving outcome-based remuneration more prominence. Gradually, advertisers would like to see the full cost chain of their programmatic buys, pushing agencies to outcome-based pay.
12. In House programmatic advertising v/s agency.
An IAB report suggests that nearly 40% executing programmatic trading via in house and 50% publishers also have an in-house model. This means advertisers are looking for more transparency, control of their ad strategies, and outcome.
It makes more sense to have an in-house team for strategizing programmatic ads and an agency partner for implementing parts of it instead of having a full-stack programmatic AdTech in house.
Wrapping up
Yes, Adtech is complicated but the best part is that it allows integrating the whole toolset into a single system. According to Zenith Media, the ad spends on digital media will reach $329 billion in 2021. However, there are major concerns and challenges -Ad Fraud, transparency, and privacy issues need immediate action.
There have been big changes and improvements over what advertisers and publishers used to have earlier but it still needs more work and their expertise to handle the challenges and resolve for good.