Is Your Business Ready for AI Implementation?

Artificial intelligence (AI) and machine learning are no longer futuristic theories. They are now real technologies with real applications in numerous businesses. The Forbes Insights poll, together with Dell Technologies and Intel, showed that AI is a key component of digital development, but only a quarter of Chief Experience Officers surveyed say they have implemented these technologies in their company. What is the reason for such low AI penetration in organizations and is your company ready to use machine learning? In this article, we will share our thoughts on the impact of AI on business and how to implement it faster.

Using AI in Business

Over the past 50 years, numerous businesses have been actively automating processes.

In the near future, we will completely get rid of the manual processing of
information and instead use autonomous systems capable of
processing huge amounts of information quickly. If businesses introduce new technologies into their workflow, they will be able to significantly improve productivity and financial efficiency.

These days, it’s not enough to just create a product or offer a service. It is also important to establish communication with your consumers. Therefore, product improvement according to user experience becomes the key to effective business. This applies to both B2B and B2C companies.

Automation, flexibility, and simplicity are terms that must be clearly
integrated into any organization's processes. Thanks to the efficient use
of resources, your company will increase customer loyalty and will have a
competitive advantage over other market players.

How can you start using machine learning?

1. Create or adjust your role in the automation process and instill a new corporate culture.
2. Assemble an ideological team of specialists who are ready to face the difficulties of mastering new technologies.
3. Prepare data for artificial intelligence training.
4. Choose a machine learning platform or service provider that provides AI as a service or develop your own solution.
5. Train your own specialists, because it will be very expensive to search for ones in the market.
6. Run, test and implement the project.

From Theory to Practice

Now, let's talk about the companies that effectively use new technologies in their strategies.

Google - Neural Networks

The company's most significant achievement is the creation of machines in DeepMind that can dream and create unusual images. Google is committed to exploring all aspects of machine learning, which helps the company improve algorithms, as well as process natural speech more efficiently and translate it, improving both ranking and predictive systems.

Pinterest - Content Search

The main function of the Pinterest social network is content curation.
And the company is doing everything possible to increase the efficiency
of this process, including the use of machine learning. Today, machine learning is involved in every aspect of Pinterest’s business operations, from moderation of spam and content searches to monetizing ads and reducing the number of unsubscribes from newsletters.

IBM - Next Generation Healthcare

IBM is abandoning an outdated business model and is actively exploring new directions. The brand’s most famous product today is Watson Artificial Intelligence. Over the past few years, Watson has been used in hospitals and medical centers where it has diagnosed certain types of cancer more effectively than oncologists.

Watson also has huge retail potential where it can serve as a consultant. IBM offers Watson as a license-based product, making it unique and affordable.

The Future of AI

1. Machines that learn even more efficiently

Very soon, artificial intelligence will be able to learn much more
efficiently: machines will improve with minimal human involvement.

2. Automation of the fight against cyber attacks

The rise of cyber crime is forcing companies to think about defenses.
Soon, AI will play an increasingly important role in monitoring,
preventing and responding to cyber attacks.

3. Convincing generative models

Soon we will not be able to distinguish machines from people at all. In
the future, algorithms will be able to create pictures, imitate human
speech and even entire personalities.

4. Quick training

Even the most complex artificial intelligence needs a huge amount of
data for training. Soon, machine learning systems will require less and
less information and time.

Final Thoughts

Unfortunately, these technologies are imperfect, and human skepticism
for their implementation is still high. A recent IDC report claims that AI and machine learning will increase productivity by 4 times in the foreseeable future, and 2.5 million industrial robots will work in industries around the world. In 2020, about 30% of all office work will be automated, and by 2021, 20% of corporate applications will be working using AI.

It sounds great, but in practice most companies still use manual labor
to process data. Their corporate culture, inertia and unwillingness
to apply new technologies may hinder business development and AI implementation.