Artificial-intelligence-in-the-enterprise.html

1. Artificial
Intelligence (AI)
and Its Impact on
Technology
Entrepreneurship
Presented by
Milan Darbar, Heena Ameena, Sai
Karthik Naraparaju
Professor. Sergei Andronikov
February 24th 2023

2. Introduction
• Artificial Intelligence, commonly known as AI, is a rapidly
growing field that has been making waves in the technology
sector. With its ability to process and analyze vast amounts
of data, AI has revolutionized the way businesses operate,
leading to the development of new and innovative products
and services. In this presentation, we will be exploring the
impact of AI on technology entrepreneurship. We will be
looking at how AI is changing the way technology startups
are creating and delivering solutions to their customers, and
the opportunities and challenges that come with this new era
of technological advancement.

3. Introduction
• Artificial Intelligence,
commonly known as
AI, is a rapidly growing
field that has been
making waves in the
technology sector.
With its ability to
process and analyze
vast amounts of data,
AI has revolutionized
the way businesses
operate, leading to the
development of new
and innovative
products and services.

4. The topics that
will be covered in
this presentation
include:
1.Overview of Artificial Intelligence and its evolution
2. AI applications in various industries and their impact on the
market
3. The role of AI in product development and innovation
4. The impact of AI on job market and the future of work
5. The ethics and concerns surrounding the use of AI in
technology startups

5. What is Artificial Intelligence?
• AI (Artificial Intelligence) refers to the simulation of human
intelligence in machines that are designed to think and act like
humans.
• There are different types of AI, including:
• Machine Learning: It is a subfield of AI that involves the
development of algorithms that allow computers to learn and
make predictions or decisions based on data input.
• Natural Language Processing (NLP): It is a subfield of AI that
focuses on enabling computers to understand, interpret, and
generate human language.
• Computer Vision: It is a subfield of AI that focuses on enabling
computers to understand, interpret, and analyze visual
information from the world.

6. Some :examples of AI applications across different industries are
Healthcare: AI Finance: AI Transportation: AI Retail: AI
Healthcare: AI is used
in healthcare for tasks
such as image
analysis for disease
diagnosis, drug
discovery, and
personalized
treatment plans.
Finance: AI is used in
finance for tasks such
as fraud detection,
risk management,
and algorithmic
trading.
Transportation: AI is
used in
transportation for
tasks such as
autonomous vehicles,
traffic prediction and
management, and
optimization of
supply chain
management.
Retail: AI is used in
retail for tasks such as
customer service
chatbots, product
recommendation, and
demand forecasting.

7. How AI is Changing the Landscape of Entrepreneurship
The benefits of AI for technology entrepreneurship are numerous. AI enables entrepreneurs to
analyze large amounts of data and make predictions, leading to increased efficiency and cost savings.
For example, AI algorithms can be used to automate repetitive tasks, freeing up employees to focus
on more strategic tasks. This leads to improved productivity and reduced costs, allowing companies
to remain competitive in the market.
However, there are also potential challenges of AI for technology entrepreneurship. One of the main
challenges is job displacement, as AI technologies automate tasks previously performed by humans.
This can lead to unemployment and economic hardship for affected workers. Additionally, there are
ethical considerations that must be addressed, such as privacy and security, data bias, and the
potential for AI to be used for malicious purposes.
In conclusion, AI is transforming the way businesses operate and creating new opportunities for
entrepreneurs. However, it is important to consider the potential challenges and ethical implications
of AI

8. Challenges of Building an AI-based
Startup
 Technical Challenges:
1. Data Collection: One of the biggest challenges for AI startups is
collecting enough high-quality data to train their algorithms. Without
enough data, AI algorithms are unable to make accurate predictions or
decisions
2. Model Interpretability: Another challenge is model interpretability,
which refers to the ability to understand why an AI algorithm made a
certain decision. When models are not interpretable, it can be difficult
to trust their predictions and decisions, which can lead to poor
adoption by users.
3. Algorithm Bias :Bias can be introduced into AI algorithms if the data
used to train them is biased in some way. This can result in incorrect
predictions or decisions that unfairly impact certain groups of people.
4. Model Deployment: Deploying an AI model in a real-world environment
can be difficult, as it requires taking into account a wide range of
technical considerations, such as scalability, security, and privacy.

9. Opportunities
for AI-based
Startups
 AI-based startups are gaining immense popularity in various industries, as they are providing
innovative solutions and making processes more efficient and effective. Here are a few examples
of opportunities for AI-based startups in different industries:
 Healthcare:
1. Healthcare is one of the largest sectors that can benefit from AI. Startups can provide AI-based
solutions for diagnosis, predictive analysis, and patient monitoring. Some successful AI-based
startups in the healthcare sector include:
2. Enlitic: Enlitic is an AI-based startup that uses deep learning algorithms to analyze medical
images and assist doctors in making more accurate diagnoses.
3. Path AI: Path AI is a company that uses AI to improve the accuracy and efficiency of cancer
diagnoses.
 Finance:
AI-based startups in finance can provide solutions for fraud detection, risk management,
and portfolio management. Some successful AI-based startups in finance include:
1. A eye : A Eye is a company that uses AI to develop advanced imaging and sensing solutions for
industries such as security, transportation, and retail.
2. Zest Finance : Zest Finance is a company that uses machine learning algorithms to provide
better credit scoring and underwriting for consumers who have limited credit histories.

10. Resources for Entrepreneurs
As Artificial Intelligence (AI) continues to be a rapidly growing industry, there are many resources available for
entrepreneurs who are looking to start an AI-based startup. Some of the key resources include accelerators,
incubators, and funding opportunities.
1. Accelerators: An accelerator is a program designed to provide mentorship, training, and resources to help startups
grow and succeed. Some popular AI-focused accelerators include Element AI, 500 Startups, and Y Combinator.
2. Incubators: An incubator is a program that helps startups in the early stages of development by providing
workspace, access to funding, and mentorship. Some of the well-known AI-focused incubators include InnoVentures,
NVIDIA GPU Ventures, and Tencent AI Incubator.
3. Funding Opportunities: There are many opportunities for AI startups to secure funding, including venture capital,
angel investing, and crowdfunding. Some popular AI-focused venture capital firms include Data Collective, Amplify
Partners, and Gradient.
• In conclusion, AI-based startups have access to a wealth of resources, including accelerators, incubators, and funding opportunities. By utilizing
these resources, entrepreneurs can gain the support they need to successfully launch and grow their AI-based businesses.

11. Case Study:
AI-based
Healthcare
Startup
 Case Study: Ada Health
• Ada Health is an AI-based healthcare startup that was founded
in 2011. It is headquartered in Berlin, Germany and operates
globally. Ada Health is an innovative digital health platform that
uses artificial intelligence and machine learning algorithms to
diagnose and provide personalised health advice to users.
 Business Model:
• Ada Health’s business model is based on offering an AI-
powered platform that provides diagnosis and health advice to
users through a mobile application. The company earns revenue
through the sale of its subscription-based service, which
provides users with unlimited access to Ada Health’s diagnostic
tool and personalised health advice. Additionally, Ada Health
has formed partnerships with healthcare providers, payers, and
employers, offering its services as an addition to existing health
insurance packages.
 Target Market:
• Ada Health’s target market is the global population of
individuals who are seeking health advice and want to better
understand their symptoms. This includes individuals who are
not able to easily access a doctor, as well as those who are
looking for a more convenient and cost-effective way to
manage their health. Ada Health’s target market is made up of
individuals from all walks of life, including the elderly, people
living in remote areas, and people who are looking for a more
accessible and user-friendly health experience.

12. Case Study:
AI-based
Finance
Startup
• The AI-based finance startup in this case study is named "Wealthfront".
• Business Model: Wealthfront operates as a robo-advisor, providing automated
investment management services to its clients. The platform uses artificial intelligence
algorithms to analyze financial data and make investment recommendations based on
individual client goals and risk tolerance. Wealthfront charges a low annual
management fee of 0.25% on client portfolios, making it an affordable option for those
looking to invest their money.
• Target Market: Wealthfront's target market is primarily the younger generation,
including millennials and Gen Z, who are tech-savvy and prefer to manage their
finances through online platforms. The company also targets high-net-worth
individuals and families who are looking for a low-cost, automated investment
management solution.
• Key Differentiators: Wealthfront differentiates itself from other robo-advisors by
offering a comprehensive financial planning platform that includes features such as
tax-loss harvesting, portfolio rebalancing, and tax-optimized direct indexing.
Additionally, the company's use of AI technology allows for more personalized
investment recommendations and risk management strategies. Wealthfront also offers
a cash management feature that provides high-yield savings accounts and debit cards,
which sets it apart from other robo-advisors who do not offer these services.
• Overall, Wealthfront's combination of low fees, comprehensive financial planning
services, and AI technology makes it a standout in the robo-advisor space, appealing
to a growing number of individuals who are looking for a convenient, cost-effective
way to manage their finances.

13. Conclusion
 Here are some general key points and discussions around the future of
AI in technology entrepreneurship:
• 1. AI is transforming the way businesses operate and the technology
entrepreneurship industry is no exception.
• 2. AI has the potential to automate many manual and repetitive tasks,
freeing up time and resources for entrepreneurs to focus on higher-level
tasks and innovation.
• 3. AI can help startups analyze data and make predictions, identify
market trends and customer preferences, and make informed decisions.
• 4. AI has the ability to provide real-time insights, personalization, and
optimization, leading to improved customer experiences and increased
revenue.
• 5. The increasing availability and affordability of AI technology is making
it accessible to more and more startups, providing them with opportunities
to grow and compete.
• 6. AI has the potential to disrupt entire industries and create new ones,
providing entrepreneurs with opportunities to innovate and create new
solutions.
• 7. The future of AI in technology entrepreneurship is uncertain, but it
presents a vast array of opportunities for entrepreneurs who are willing to
embrace and harness its power.
• 8. It is important for entrepreneurs to stay informed about the latest
developments in AI and to understand how it can be leveraged to create
new business opportunities.

14. References
• Provide a list of sources used in the presentation (e.g.,
articles, reports, websites)
• Include URLs for any online source.
• Gartner. (2019). Artificial Intelligence: Hype vs. Reality.
Retrieved from https://www.gartner.com/en/information-
technology/insights/how-to-navigate-the-hype-and-reality-
of-ai.
• McKinsey & Company. (2019). Artificial intelligence: The
next digital frontier? Retrieved from
https://www.mckinsey.com/business-functions/digital-
mckinsey/our-insights/artificial-intelligence-the-next-
digital-frontier.
• Deloitte. (2018). The State of Artificial Intelligence in the
Enterprise. Retrieved from
https://www2.deloitte.com/us/en/insights/focus/tech-
trends/2018/artificial-intelligence-in-the-enterprise.html.