Google organizes the Google I/O event every year. This year, it was on May and the announcements from the tech giant turned many heads as usual. The company evidently is sticking to their approach to implementing ‘smarter’ online services by leveraging Artificial Intelligence. Most of Google’s announcements can have a deep impact on a number of sectors including software and mobile application development.

Here are a few major highlights from this year’s Google I/O.

Google Search powered by Camera and featuring AR capabilities

The I/O 2019 keynote started with the company’s announcement to imbue AR capabilities into Google Search and also bringing Camera into the equation. This could mean a lot of things for businesses; particularly on their SEO front. Retaining customers and a great search engine presence would require them to embrace AR technologies as well.

Google Duplex on the web

The search engine giant introduced Google Duplex as an AI-powered voice assistant capable of making calls and conversing like humans. Everyone loved it but many criticized it for being only a mobile-only augmentation. Seems like Google heard the demand as the company announced Duplex on the web on the 2019 I/O. Voice-based web chats will be made available for car rentals and movie bookings in addition to restaurant bookings and hair-styling appointments.

Android Q Beta 3

Everyone expects Google to share something ‘Android’ on Google I/O. And they did reveal a few things about what Android Q Beta 3 will feature. The company revealed that a ‘dark’ theme would soon be made available for Android Q devices which can cut down battery utilization. Additionally, the ‘Smart Reply’ feature in Android Q will also be accessible within third-party messaging apps.

Project Mainline

Probably the most intriguing of Google’s projects, Project Mainline aims to update 12 core components in Android. These components were thought to impossible to update till now without a major software upgrade. In this year’s I/O 2019, Google shared the purpose behind launching Mainline which involves reducing the number of times users have to update an app and also to reduce the size of apps.

Real time on-device captioning for videos

One of the most exciting announcements made by Google this year at I/O 2019 is Live Caption; a feature that brings real-time on-device captioning for all types of media without an internet connection. Users watching offline YouTube videos and stored video content on their device will get live captions without a data network enabled.

Faster, uninterrupted app updates

Many businesses may have encountered the challenge of a declining app user base when they release mandatory updates for their apps. Google announced in the event that they have an in-app API update in the works that will allow users to update apps without leaving the app. This way, users will get uninterrupted services from their apps while the updates are taking place.


The Google I/O Event never fails to bring with it a number of changes in Google services, SEO and Android app development trends. It’s the same this year as well. The highlights mentioned in this blog are just a few that we picked out of our excitement.

If you are wondering about the impact of changing trends on your business and its mobile app, drop a message to the experts at AOT. We can help you understand how changing trends can be of benefit to business app development.

The fast-paced evolution of technology brought us a number of wonders; one of which being Artificial Intelligence. Many global industries have been experimenting with AI to enhance their business processes and garner unparalleled competitive advantages. Even with its proliferation, AI is still considered to be in its infancy, and everything we see now is just the tip of the iceberg.

It’s most common use case is for personalization. For instance, Netflix – a popular streaming service features an AI-powered algorithm tracking the preferences of its users. This is why you get great content recommendations – videos that you likely want to watch the next time you launch the application. AI is also how Amazon recommends products that users end up buying eventually – all based on the users’ purchase history and browsing behavior.

AI in SMarketing

For modern businesses, Sales & Marketing aren’t two separate departments. It’s all SMarketing now, where teams from each departments collaborate to increase brand exposure, brand reputation, sales figures, and consequently business revenue.

Marketers of such businesses that are willing to go an extra mile are already leveraging Artificial Intelligence to enable accelerated business growth, improved revenue, and personalized customer experiences.

The business’ target audience thus gets curated content delivered to them at the right time featuring carefully crafted messages and curated recommendations. This typically ends up in a purchase if the content triggers an immediate interest. And such tactics are only an option thanks to AI.

Artificial Intelligence is expected to essentially align sales and marketing in a healthy pipeline that delivers the best results.

That said, let’s check out the AI trends that are significantly influencing sales this year.

1) Advanced Analytics

The key to winning new customers and satisfying existing ones is analytics. Proper analytics involves implementing test cases, measuring results, uncovering patterns and deciphering insights.

That was the story till AI came into the picture. Modern businesses now utilize advanced analytics powered by AI algorithms to get deeper, more accurate reports and forecasts. Savvy marketers are investing in AI-driven predictive analytics for more rewarding human interactions and for mitigating risks that impede faster business growth.

2) Voice-enabled Smart Apps

Chatbot Assistant is the next big thing in the business realm. AI-powered chatbot assistants go up a notch when it comes to offering recommendations to a business’ customers, helping them with their queries, and even encouraging them to make purchases with personalized offers.

Voice Assistants don’t have human limitations. They can be of service to customers 24/7, and can be controlled via voice commands from authorized users. The possibilities are many and the scope is vast. AI-augmented voice assistants are certainly proving to be worthy assets for businesses to invest in.

3) Predictive Lead Scoring

Spending time nurturing leads with little to no growth potential can do a lot of damage to an organization – missed targets, demotivated sales teams, dwindling revenue etc. This issue can be sorted out with AI integration. Augmented with Machine Learning capabilities, an AI solution can efficiently analyze leads and offer predictive lead scoring.

As the data increase, the accuracy of predictions also increases. This would make it easier for the sales team to identify leads that are more likely to convert and those that are less likely to convert.

4) Improved Sales Forecasts

Back in the days, it was humans who came up with sales forecasts. Now it’s an AI element, and one of the main reasons why many businesses invest heavily in AI technologies. With AI, businesses can make use of the tremendous amounts of data they generate by transforming them in meaningful insights that in turn deliver accurate sales forecasts for maximum profit.

Sales forecasts aren’t based on hunches and customer emotions anymore. Instead it’s driven by a data-oriented rationale which we will be seeing a lot more amongst businesses in the coming months.

5) Personalized User Experiences

Probably, no organization in our world does it better than Google. The search engine giant so far is one of the biggest investors in AI technology, and is among the most successful organizations when it comes to leveraging Artificial Intelligence to serve people.

With Rankbrain, a Machine Learning program, Google constantly monitors and analyzes user engagement to continuously provide better search results to users regardless of the search query. This way every kind of information would simply be a Google search away. The organization’s personalization features have a lot to do with their use of AI. AI is also a core element behind Google Ads.

Businesses can apply this technique on their own operations to personalize their content and offers to customers; both new and existing, resulting in a greater number of conversions and generating more leads than ever. This trend isn’t relatively new but it only gained traction recently.

A great example would be to offer discounts to a visitor who left a website after adding an item to the online shopping cart so that he completes the purchase. The offer can be personalized based on that particular individual’s purchase history on the website and even the purchase frequency. Mind you that this entire process can be automated with AI leaving the business’ sales team free to tackle bigger challenges.


For modern businesses, the stakes are higher than ever when it comes ‘SMarketing’ in dynamic, highly competitive markets. The smallest mistake could end up breaking the business and the smallest detail could speed up the business’ growth and revenue. For businesses that are looking forward to a stable and economically feasible future, AI should be an integral part of their sales, marketing and operations.

The AI trends mentioned in this blog aren’t all new but are slowly becoming an industry standard for businesses willing to invest in retaining their competency during changing times. As a matter of fact, many businesses vouch for AI’s potential when it comes to improving the quality of leads, delivering personalized content to the right people at the right time, and even in devising profitable business strategies on competitive markets.

If your business is ready to jump on the AI bandwagon, AOT can help you make that leap in the best way possible. Get in touch with AOT’s AI experts to start off on the right foot.

Vector image created by macrovector –

Face recognition is not a new feature. But it’s one of the most important use cases of Artificial Intelligence today. Organizations use face and image recognition features to deliver memorable digital user experiences to people. The face recognition feature is quite common nowadays in the form of mobile biometrics. Image recognition features are more prevalent in social media networks.

The market for Face/Image recognition is growing evidently, and is estimated to be close to $10 billion by 2023. With AI powering it, the technology can recognize people just like a human brain can. Back in the days, it wasn’t easy for mobile app developers to implement this feature in web, mobile or desktop apps. But now, there are qualitative APIs that can help them get it done effectively.

Here are a few popular ones that app developers should try out at least once.

Amazon Rekognition

Amazon Rekognition is an image/video recognition tool that can analyze image and video files in Amazon S3. The API is powered by deep learning technology developed and owned by Amazon.

Key features include:

  • Face recognition in videos and images
  • Facial analysis to determine emotion, age range etc.
  • Text detection in images
  • Unsafe content detection
  • Object/activity detection


Kairos is another popular face recognition API that utilizes a potent combination of computer vision and deep learning to recognize faces in videos, images, and in the real world.

Key features include:

  • Face recognition and identification
  • Gender and age detection
  • Multi-face detection
  • Diversity recognition

Microsoft Computer Vision API

A widely used API developed by Microsoft, the Computer Vision API can process visual data in real-time and possesses machine-assisted image moderation capabilities. Developers use this API to implement a feature that lets the application identify people who were previously tagged in images.

Key features include:

  • Image analysis
  • Real-time video analysis
  • Text detection in images
  • Read handwritten text in real-world environments
  • Recognize over 200,000 celebrities and landmarks

Watson Visual Recognition API

The Watson Visual Recognition API deserves to be on this list as it’s a favorite for a lot of developer communities in the web. The API enables tagging, classifying, and searching visual content using deep learning algorithms. Another great feature is that the Watson Visual Recognition API can be integrated with Core ML to build complex iOS apps with computer vision and analytics capabilities.

Key features include:

  • Analysis of object, face, explicit content etc.
  • Pre-defined image analysis models
  • Creation of custom models that can be trained

Google Cloud Vision

Google Cloud Vision features a number of pre-trained models for impressively accurate image recognition and analysis. The API allows developers to build use case-based custom models using AutoML Vision.

Key features include:

  • Wide array of pre-trained models ranging from transportation to wildlife
  • ML Kit integration for Android iOS app development
  • Handwriting, face, and landmark detection
  • Explicit content detection
  • Sentiment analysis


Even with the right tools and APIs, implementing face and image recognition features in apps is a complex process. In addition, this also requires trained AI/ML models. To conclude, all this and more can be done only if the developer has great expertise in leveraging AI and app development. AOT has proven expertise in developing complex AI-driven mobile apps for Android and iOS platforms. If you are planning to utilize a next-gen app with facial/image recognition features, we can help. Get in touch with us to check out our track record.

Image created by pikisuperstar –

Artificial Intelligence is now seen as a critical component for enterprise digital transformation. AI can take many forms to help businesses achieve accelerated growth and improved operational performance in highly competitive markets. Among the various forms of AI, voice interfaces are probably the most demanded. For businesses, an AI-driven voice interface is known by a different name – Conversational AI.

The benefits of conversational AI seem to be expanding without limit as AI continuously evolves. From improving customer service to increasing online sales revenue, the wide array of benefits granted by conversational AI are what businesses are willing to invest in.

As a matter of fact, Gartner predicts that by 2020, 25% of customer support & service operations will be driven by virtual assistants across various engagement channels.  

So the question now isn’t about how a company should implement conversational AI. It’s more about where they should start. That said, this blog covers a few major aspects that make a great conversational AI app. Make sure your journey to implement and leverage conversational AI is along the right course.

Implementation efforts centered on the business case

Before you start implementing conversational AI for your business, make sure that you can articulate the business case as well as the returns you expect from the technology. If you aren’t sure about the latter, work collaboratively with your AI services partner to help define the value you would like from your conversational AI.

With your efforts centered on the business case and the expected value, it’d be easier for you to deploy the right technology by making the right design decisions. The key is to stay true to the defined goals. As long as you are sure of the desired result, you can shape the implementation properly while taking into account the business constraints such as time or budget. This way your tech will only possess features that your business really needs.

A UX that streamlines customer journey

The AI-based solution’s adoption and revisit rates depend on a number of factors out of which the UX is possibly the most important. Even if the conversational AI solution features attractive dialogs and integrated data that facilitates personalized responses, it would still appear underwhelming if it lacks a solid user experience.

For a conversational AI, the UX needs to take a few major factors into account. The solution should speak and converse like a human. This doesn’t mean it should pretend to be one. Users may expect digital customer support employees to participate in small talk, remember, understand context, and be smart.

Many companies try to use chatbots that pretend to be humans when interacting with potential customers. This is likely to backfire as the approach can break the trust the end users have on the solution. The conversational app should be able to resolve the user’s issue. If it fails to do so, the user will approach a different channel with a better alternative that can serve them better.

Information pertaining to things that are out of scope for your intelligent bot should be provided early on in your customers’ journey; at least as links. The personality of the bot is also important. It can be humorous, sassy, or formal with a rich UI coupled with modern design standards.

The key is to have the conversational app cover the user journey from the beginning to the end while drawing out a satisfactory conclusion for users with their issues resolved.

A scalable platform that can handle multiple intents

When going for an AI-driven conversational bot, it’s best to start small. Implement the idea as a small project and develop it further in phases after assessing the initial results. Choosing a scalable platform here is a great approach that helps you capitalize on your initial investment and gives you a lot more options when moving forward.

The user will want to achieve something with the app, right? There will be an ‘intent’. You should ask yourself how many intents your chosen platform can handle. Various conversational AI platforms have different capacities when it comes to handling intents. The platforms will have different algorithms to process the intents. Though Machine Learning capabilities make it easier for conversational AI applications to learn intents, such features still won’t be enough if there are hundreds of intents over multiple business departments, divisions, languages, and geographic regions.

There are platforms that are powerful enough to deal with a large number of intents but there tends to be a limit at present which forces enterprises to develop multiple solutions to get by. The bottom-line here is that the conversational AI platform should be capable of delivering precise responses depending on user intent and context. It’s not easy but it is practical provided the chosen platform is highly scalable.

Top-notch security and encryption standards for customer data

Conversational data can be a goldmine in disguise for businesses. Such data can be analyzed and understood much easier than the data gathered from calls. However it also presents a great risk to organizations. They will need to secure the data and ensure the privacy of their users. Any compromise in the conversational data could end up causing your customers to lose trust in your business instantly.

The AI solution should be capable of anonymizing the data while also making it easier to understand the intents for analytics. The identifiable data can be replaced with placeholders. This way the customer identity will remain anonymous while the intent will be clear to your organization for analytics purposes. If there are transactions involved, the application should have robust encryption mechanisms to encrypt the data that would be transmitted over the internet.

Your organization should be certain about the information you wish to collect from customers, the security practices that can be implemented to safeguard the data, and practices to make good use of the data without compromising the privacy of customers even before building a conversational AI application.

The value of the AI solution depends on its capability to continuously learn and improve. Building one such solution requires great proficiency in AI and associated technologies and years of experience in building enterprise-grade business solutions. AOT has both, and we can help you utilize a powerful conversational AI program as well. Talk to our experts today to learn more.

Image created by fullvector –

Google stands out among all the corporate giants actively attempting to leverage artificial intelligence efficiently, evident from their recent I/O where they revealed that Google AI is now capable of making real life conversations – a disruptive evolution of AI that’s turned many heads this year. Of course, the advancement would soon enhance mobile experiences which is exactly what modern consumer lifestyle demands.

Consumers today spent more time on mobile devices compared to televisions or desktops. This is reflected particularly in eCommerce, with many studies finding a steady growth in mCommerce sales.

Statista projects global mCommerce revenues to exceed 660 billion US dollars this year.

mCommerce is the key to the success of eCommerce retailers today, and optimizing it with AI minimizes associated risks while boosting the business’ growth. AI-infused mCommerce sites get a number of cool features – from automated reasoning capabilities to advanced customer behavior patterns analyses and predictions.

That said, here are a few ways how eCommerce businesses can optimize their mCommerce with Artificial Intelligence.

Personalized recommendations

Basically, what you always see in mCommerce apps like Amazon. You get recommendations based on your browsing patterns and previous purchases. For a mCommerce business, upselling and cross-selling are great ways to boost sales by enticing existing customers. This can be performed by powerful AI solutions that analyze customer behavior, preferences, and footprints to figure out the products that they would be interested to check out.

Personalized push notifications

Push notifications are sometimes that which triggers a purchase from a potential buyer. For instance, buyers who had to leave before checkout can be reminded of their abandoned cart with push notifications later. AI engines can do this and more. They can identify customer preferences and use tailored push notifications to target prospects who are more likely to buy certain products, and also re-engage existing customers.

Virtual assistants

Over the years, virtual assistants have become smarter and more versatile facilitating result-oriented, fluent interactions. Virtual assistants make a great addition to mCommerce platforms providing a much more convenient, easy, and interactive shopping experience to customers, and increased conversion rates for the mCommerce brands. With AI-driven virtual assistants, customers need only launch the app and ask the assistant to place an order for a particular item.

AI-powered chatbots

Unlike the virtual assistant, chatbots are present to provide support to customers who came across some kind of issue while trying to make a purchase. Many customers are likely to have queries regarding the products they intend to buy. In a modern mCommerce store, chatbots should be there to answer customer queries, and offer human support if necessary.

There are many AI solutions in the market today like Botsify, etc. that allow brands to create and train their own unique chatbots easily and integrate them into their mCommerce site. These chatbots have self-learning capabilities that make them better as more data are fed to them.

AI-based price negotiation

Shopping cart abandonments are one of the biggest problems eCommerce stores encounter. One of the major reasons for such issues is the fact that users cannot negotiate product prices in a mCommerce site unlike brick and mortar stores. As an alternative, users tend to research competitor stores to see if the item they seek is available with a smaller price tag.

The advancements in AI today can present solutions to this particular problem in the form of an AI-based mediator system. The solution can interact with the prospects, analyze their purchase histories and interests, and determine a strategic discount offer they’d be interested in. This can get reluctant prospects back on board and finish a purchase.

Voice & image search

If it’s an eCommerce store, there must be a ‘Search’ option, especially if the store has thousands of products under various categories. The traditional text-based search option is almost outdated now, and is being reinvented by harnessing AI. AI-powered voice search and image search features have already started taking over, and are being welcomed with praise by online shoppers.

Voice search services like Inbenta, Klevu etc. recently gained much momentum across eCommerce platforms. Though not always accurate, AI-driven voice search feature has a 95% success rate according to studies.

Traditional image search, on the other hand, has evolved into visual search today thanks to AI. There are machine learning algorithms available that can interpret visual data with impressive accuracy. This essentially redefines the shopping experience of mCommerce customers. All they need to do is use their mobile cameras to snap pictures of an item they see in real life. The AI-based visual search algorithm can then match objects in the image, and perform a search for the item in the image on the linked database.

AI-AR powered visualization capabilities

Augmented Reality entered the scene when mCommerce brands started looking for ways to reshape mobile shopping experience for customers. AR, by that time, already made its mark in the form of Pokémon GO. Now the trend is to combine AR with AI resulting in interactive AR applications with an intelligent AI core.

Deloitte’s Digital Identibot managed to combine both technologies to deliver an impressive experience, though the solution isn’t commercially available yet. The point is that today it’s possible to combine AI and AR thanks to a plethora of readily available tools, frameworks, and platforms.

The AR development community is steadily growing, and people keep coming up with creative ways to use the technology in various industries. Google’s ARCore and Apple’s ARKit are two great SDKs that can help aspiring AR developers build innovative applications for eCommerce stores.


Ease of use is what made mobile devices so important for people across the globe, and ease of use is what they expect when doing something on said devices – be it seeking information or shopping. Prioritizing mobile users’ convenience and securing their transactions are the key for a mobile app’s success. For mCommerce stores, all of this and more is possible by harnessing artificial intelligence.

If your mCommerce site still hasn’t channeled AI yet, it’s time to rethink your mobile sales strategy. AoT technologies can help you wield AI the right way so your brand always stays ahead of the curve. Give us a ring to learn more.

Image Designed by Freepik