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6 Ways to Improve your Business with Artificial Intelligence

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Artificial Intelligence is the technology that bestowed us with a fairytale-like functionality in our homes and offices. Have you seen the “ Beauty and the Beast� movie? In that movie, the beauty was in the beast’s castle, and there was no other living creature there. She was all alone, except she had a talking and moving clock, a candelabra, a teapot, and a teacup. Here are six ways to improve your business with artificial intelligence.

Science didn’t make the magic happen at the Beast’s Castle — but science has developed something close to it for us.

The wonderful technology that can make our lives easier is known as Artificial Intelligence — and you can talk to it, too.

The simplest example of artificial intelligence is Alexa and Siri. Imagine calling someone when Siri was not there. You have to find their name in the contacts, and then you have to dial them up. Now, you can simply say, “ Hey Siri, call XYZ,� and Siri will call them.

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Artificial Intelligence for Business

As technology is increasing, the demands of users are also increasing. It is becoming hard for businesses to keep up with those demands. If a business wants to grow, they have to come online. Having a business app or website is that you cannot just launch a website/app and not have online support. You have to track who visits your website/app, and you have to do something to convert that potential client into a real client.

But the thing here is that you or your support guy cannot be online 24*7. If a user comes midnight to shop or have an inquiry and message you, you have to reply within a minute or at most in 5 minutes, or else they will leave your site/app. This is a task that is not possible, but deep down, you know that this is a matter that does need to be solved.

In this case, conversational AI can be used that can trigger a reply once they come across a keyword. If they encounter something unknown, they can simply answer that please provide your email address or phone number, and the team will contact you as soon as possible. At least some reply is better than nothing.

Moreover, if you add enough keywords, the conversational AI can talk like a support person. Dish Network has tested this thing, and in their observation, customers rate interactions with virtual agents the same, and sometimes even better, in comparison to the human support staff.

When a machine does work, it is error-free. Moreover, if you let the machine do the job, you will get more time to do tasks that require human interaction. This way, you will enable yourself to do more important tasks and work productively. As a startup or a small business, this can be the competitive gain that you were looking for.

Let’s have a look at how you can improve your business with Artificial Intelligence.

6 Ways to Improve your Business with Artificial Intelligence

1. Effectively target your market

We have so many marketing ideas, but the main reason why many of them don’t work is that we cannot target the right audience. As a content writer, I was writing a blog about cloud computing, and from that day, Google started showing me ads for cloud computing. I am not a buyer here, but as I searched for the same, Google thinks I am interested in buying the same.

This particularly shows that the wrong person was targeted. It is possible they had an awesome offer, but cloud computing is something which I think I never have to buy. The company paid for that to be shown to the right audience, and that didn’t happen.

AI can release you from the stress of targeting the right audience. It’ll target the right audience for you, and there are minimum possibilities of AI to go wrong. This is the feature that most of us need, as finding the right audience is a great challenge.

2. AI helps shopping

Take the phones of two different persons and go to the Amazon or Flipkart app, and you will see the difference.

Different products would be shown on their main page, and this is how people want to experience online shopping. They offer lakhs of products, and no one wants to see what they are not interested in. This is where AI stores what they like and thus show them the related products.

Now, AI is completely changing how people shop online. One of the reasons that people prefer traditional shopping was that they were able to try the clothes at the shop and they were able to see if it suits them or not. Thanks to Augmented Reality, people can now take the trail online.

People can now take a trail of the clothes that they want to buy, and thus this is making their experience more pleasant.

3. Personalized experience

AI is centralized towards creating an awesome customer experience. This helps companies to earn more as customers are willing to pay more for a better customer experience. A simple example is that we pay more when we go to a salon for a haircut, and we pay less to a local barber, and then we even ask for discounts. The willingness to pay is dependent on the experience.

Therefore you should try to create a pleasant customer experience as you can. According to a report by American Express: “ Customers who have a positive customer experience spend 74% more�.

4. Content generation and curation

This feature is one that threatens my job. AI can even write content that is plagiarism-free and filled with the right keywords, and thus they can rank on the google pages.

AI can create eye-catching content. But it is hard to create content that does not contain any plagiarism as facts and studies will remain the same, and if someone uses these facts in their content, this will lead to plagiarism. This gave birth to automated journalism. In this, robots will write the content.

The best example is Heliograf of Washington Post, which has written various articles on the Olympics and politics and has also won awards in Artificial Intelligence.

5. Image recognition

Product tagging and visual search have started taking digital marketing with an impact. Google first founded this, and it was a wow feature. You just have to start your camera and point it to something, and then you can know what it is.

This means that if someone is looking at your product and don’t know what it is, they can just start their camera, and they can know the name and the price of the product. Thus, if someone likes your product and wants to buy it, they are just a camera search away.

This makes it easy for people to find your product and your business.

6. Voice SEO

Technology has become so advanced that phones can identify human voices and address their command. This is not unknown to people due to Siri and Alexa, but still, people cannot use it to their advantage.

Whenever I scroll through Instagram, I do come across some post with an amazing song or beat, but I don’t know the name of, but I liked the song, and I want to listen to it, but how can I do that?

The simple answer is to use Shazam or ask Siri to identify the song. It is no longer limited to mobiles. You can also use your speaker to do so.

You should understand that voice search is very different from traditional search. SEO for voice search requires a different approach. Here, long-tail keywords can help your SEO.

With the help of AI and good advertisement knowledge, ads can be personalized according to the targeted customer.

Conclusion

Artificial Intelligence can help in business by doing your work in an error-free way. It can help you in cutting down your expenses, and it can perform the work faster. You can use Artificial intelligence as the ultimate weapon that you need for competitive gain.

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Challenges of Adopting AI in Businesses

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Over the past decade, the discussion surrounding Artificial Intelligence has made waves and garnered more attention. Businesses are working towards adopting AI to harness its potential, but it comes with its challenges.

AI is now a hot topic of discussion in the business world, with big guns like Google, Netflix, Amazon, etc, benefitting largely from AI solutions and machine learning algorithms. Not just large businesses but small and medium based businesses too.

In fact, by 2025, the global AI market is expected to be almost $126 billion, now that’s huge.

There has been pressure on businesses to adopt AI solutions to get ahead. With a plethora of articles proving why it’s important to integrate AI in business practices. Because AI has proved beneficial to the successful running of businesses.

An Accenture report revealed that AI can increase business productivity by 40% and boost profitability by 38%.

However, we can’t be blind to the challenges adopting AI has posed for businesses. These challenges make the idea of the successful integration of AI seem far fetched or even unattainable.

An Alegion survey reported that nearly 8 out of 10 enterprise organizations currently engaged in AI and ML projects have stalled.

The same study also revealed that 81% of the respondents admit the process of training AI with data is more difficult than they expected.

This has shown that the expectations for businesses adopting AI might be different from reality.  

Below are the top 7 challenges businesses face in the journey of AI implementation.

1. Data Challenges

I bet you saw that one coming since AI feeds heavily on data. 

However, there’s a lot that can go wrong with the required data for AI. Factors like the volume of data, collection of data, labeling of data, and accuracy of data come to play.

Because, for successful AI solutions, both the quality and quantity of data matters. AI needs vast amounts of data for optimum performance, and a refined dataset to arrive at accurate predictions. 

According to a 2019 report by O’Reilly, the issue of data was the second-highest percentage in ranking on obstacles in AI adoption. 

AI models can only perform to the standard of the data provided, they can’t go beyond what they have been fed.

There are different data challenges that businesses face, let’s begin with the volume of data.

 Volume Of Data

The amount of data required by AI to make intelligent decisions is beyond comprehension.

Undoubtedly, businesses now generate more data compared to before, but the question arises, do businesses have enough data to feed AI?  

Businesses don’t have enough data to satisfy AI, especially when there are limitations in data collection due to privacy and security concerns. 

The same Allegion report revealed that 51% of the respondents said they didn’t have enough data.

This challenges the data infrastructure of most businesses. Businesses now need to generate more data than usual

To fix this, companies should ask: Is their present volume of data enough for the AI model? How can they generate more data?

Businesses need to know their current data acquisition and ways to acquire more data to match their AI model requirements. 

Businesses can acquire more data through the use of external data sources like Knoema which provides 100 million time-series datasets. Also, the use of carefully created synthetic data is helpful. 

Evaluating the current volume of data a business generates in comparison to what AI needs would open doors for data expansion ideas.

Collection of Data 

There are quite a number of issues that come with the collection of data. 

Issues like inaccurate answers, insufficient representatives, biased views, loopholes, and ambiguity in data are major factors that affect AI’s decisions. 

For example, the AI bias controversy that has sparked a grave concern.

Gartner predicted that 85% of AI projects will deliver erroneous outcomes due to bias in data, algorithms, the teams managing them, etc. 

There has been an outcry of AI being biased against women, people of color, etc. However, AI is not a conscious being and can’t form opinions, it only acts based on the data available. 

Therefore, this is the fault of humans, because data is provided by people, and people can be biased and stereotypical. 

This usually occurs due to the mode of data collection, data collected can’t represent everyone. 

This limits the wealth of data AI has at its disposal, leading to inaccurate decisions.

ML models require error-free datasets to provide accurate predictions for successful AI solutions.

Businesses have to employ efficient techniques and processes for collecting data.

Labeling of Data

AI relies on ML’s supervised learning to arrive at conclusions. Therefore, data needs to be labeled, categorized, and correct to use AI models.

AI’s data requirements make it difficult to efficiently label data, 96% of enterprises (insidebigdatadotcom) have run into problems with data labeling required to train AI.

The use of web-based data labeling tools can be employed. For example, the Computer Vision Annotation Tool (CVAT), which helps in annotating images and videos. 

2. Transparency Challenges 

In simplest terms, how does AI work? It arrives at conclusions and makes predictions with the data provided through the help of ML’s algorithms. 

Sounds simple right? Well, that’s not all. 

For complicated AI decisions, corporations will begin to experience the black box problem, this is where the picture gets blurry.  

The black box model is not clear on how it arrived at a certain conclusion, this leads to distrust and doubts about AI’s accuracy.

Because of the validity of the prediction or current suggestion is questioned. 

The rationale behind AI’s decisions needs to be transparent in order to build trust with businesses. 

  1. That’s why they need for explainable AI continues to grow as this makes adopting AI challenging for businesses

and has to be given more attention.

Although, the LIME (local interpretable model-agnostic explanations) approach has been helpful towards solving this problem.

3. Workforce Reception Challenges 

The non-technical workforce can find AI integration intimidating since its usage requires advanced training. 

So seamless usage and normalcy of AI in the workplace is a difficult goal to achieve. 

AI’s adoption can pose a state of confusion amongst employees. Questions like what is the need for AI? How to use this technology? Which of their responsibilities is the AI going to take over? arises. 

Despite numerous insights on how AI is not the enemy and not here to replace people, the role of AI remains misunderstood. 

The instant a business adopts AI, employees feel threatened and incompetent. 

Employees begin to feel a sudden pressure to prove their relevance. They will feel like they are in constant competition with a machine, this negatively affects the workplace vibes. 

Educating employees on what AI adoption means for the business and them overall, will help in preventing false assumptions or unrest amongst staff.

4. Expertise Scarcity Challenges 

Expertise scarcity is a major challenge in adopting AI for businesses. Also, it’s hard to hire the right people since most adopters don’t know the technicality that involves AI.

According to Deloitte’s global study of AI early adopters, 68 percent report a moderate-to-extreme AI skills gap.

AI is a growing and evolving technology, keeping up with its complexities and needs is a major problem for aspiring adopters.

The scarcity of AI’s skill set is one that hinders a successful business adoption of AI solutions. 

A survey by Gartner revealed the biggest challenge in AI adoption to be a lack of skills  

According to Deloitte, by 2024, the US is projected to face a shortage of 250,000 data scientists, based on current supply and demand. 

A prerequisite of a successful AI adoption is the use of Data Scientists.

However, hiring one is a challenge, except a business decides to outsource its AI projects. 

Also, businesses can use AI platforms with no requirement for a data scientist, else they will need to carefully and cautiously invest in a data scientist.

One of the solutions to this problem is education, educating the technical team will pave the opportunity to have citizen data scientists.

Businesses have to prioritize educating themselves of this technological industry if at all they desire a successful AI adoption.  

5. Expectations vs Reality Challenges 

There’s a lot of hype about the possibilities AI poses for businesses. When business owners consume the vast information out there containing the promises of AI, their expectations go beyond reality.

They forget that AI is a journey, not a destination. This makes businesses ignorant about the challenges that come with adopting AI. 

The confusion then sets in on what AI solutions their business actually needs, it’s important to know that AI is still growing and it’s not here to do everything for your business. 

Unfortunately, many businesses jump into the bandwagon of adopting AI with no blueprint on what they need AI for.

Also, how prepared are they to implement AI in their activities?

An AI business strategy should include which AI possibilities align with its current business goals, and preparing the business to adopt AI. 

Factors like the current capacity and expertise of business technology and data infrastructure are paramount to successfully house AI models. 

If this part of a business is weak and lacks the necessary efficiency, their reality will not match their expectations.

6. Business Use Case Challenges 

Prioritizing the area of AI application in the business is one of the common challenges whilst adopting AI. 

AI solutions are vast, however, businesses find it hard to prioritize or select the most important problem to get started with and see ROI. 

A survey by Gartner revealed that AI was mostly used either to boost the customer experience or to fight fraud. 

In the bid to play it safe and experiment, businesses limit AI to a small part of the business that brings very little impact to the business revenue. This leads to the inability to see the ROI of AI in business. 

A report by RELX revealed that 30% of the respondents cite an unproven return on investment (ROI) in AI adoption. 

Because adopting the solutions of AI and Machine Learning is a serious investment, and one with great expectations of a high level of ROI. 

According to IDC, the top AI use cases based on the 2019 market share were automated customer service agents, sales process automation, and automated threat intelligence and prevention systems.

7. Budget Constraints Challenges 

Not all businesses have the resources to invest in AI models.  

According to a report by Harvard Business Review, 40% of executives say an obstacle to AI initiatives is that technologies and expertise are too expensive. 

The same RELX report also disclosed that 50% of companies that have not yet adopted AI cite budget constraints as the primary reason. 

Small business enterprises can tap into free and paid simple AI solutions. Large businesses that want to create tailor-made solutions to fit their business use cases,

But for businesses looking to create tailor-made solutions to fit their business use cases, they are bound to experience budget constraints 

One of the solutions to managing AI budget issues is to outsource AI projects than carrying it out in the house. 

Also, enterprise software vendors and cloud providers provide ready to go AI services to curb Infrastructural costs. 

Conclusion

Adopting AI is challenging for businesses but definitely worth the effort because AI is here to stay.

These challenges will cease to become obstacles as AI becomes normalized and prioritized over time.

AI promises and possibilities can be exciting and distracting altogether. So don’t get too excited that you don’t create a clearly defined path to accomplish those solutions. 

Before investing time and money in AI, it’s important to make your business ready in every possible way to work with AI. 

Preparing your business for the change and disruption AI is about to bring is crucial.

We are habitual beings, breaking employees out of their work routines to adopt AI is a challenge, hence the need for a planned strategy. 

Having a deep and healthy understanding of what AI means for your business is a good sign of your readiness to adopt AI. 

Finally, applying AI in the core parts of your business will help to track, and measure the ROI of AI implementation to give you a clear picture of AI contributions to your business.

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