What is Generative AI for Businesses And Where is All the Hype Coming From?
Generative AI (GenAI) is a rapidly evolving field with various technologies at the AI software development core. AI foundation models, trained on massive datasets, are like prediction algorithms forming the backbone of GenAI.
The launch of ChatGPT in late 2022 fueled investment and competition in GenAI-powered virtual assistants.
However, Gartner’s Hype Cycle for Generative AI in 2023 suggests many GenAI technologies have already reached the peak of inflated expectations.
Gartner predicts significant growth in GenAI adoption across industries. By 2026, 75% of businesses are expected to use GenAI for synthetic customer data creation, compared to less than 5% in 2023.
Domain-specific GenAI models tailored to businesses and industries will also rise. Open-source GenAI models are gaining traction, offering advantages in deployment flexibility and control over security and privacy.
By 2028, energy-efficient methods are expected to optimise 30% of GenAI implementations.
Let’s take a closer look at what we’re talking about:
Domain-specific GenAI models are artificial intelligence models built for specific business domains or industries. They help businesses by providing more accurate and relevant solutions for specific tasks in a particular domain which improves efficiency and results.
Open-source GenAI models (Open-source GenAI models) are open-source artificial intelligence models that can be freely used and modified. Businesses benefit because such models offer flexibility in deployment and control over data security and privacy.
Energy-efficient methods for optimising GenAI reduce energy consumption using artificial intelligence models. These methods can help businesses reduce energy costs and make their AI solutions greener and more cost-effective.
Savvy companies are taking advantage of GenAI by creating programs to educate employees about this technology. These programs help people understand how GenAI works and how it can benefit the business.
Once employees are up to speed, teams can brainstorm ideas for using generative AI for business to solve problems and create new opportunities.
The good news is that more and more businesses are adopting GenAI. A recent survey showed that nearly two-thirds of organisations already use GenAI in multiple departments.
This trend will only continue as businesses discover the many ways that GenAI can help them succeed.
In What Business Areas AI Has Performed Best
1. Marketing & Sales
AI excels at customer interaction, targeting, and conversions. Predictive analytics, customer segmentation, and recommendation systems assist organizations in understanding and meeting the demands of their customers, resulting in more effective marketing, greater satisfaction, and improved revenue. AI automation in many areas also improves efficiency and lowers costs.
2. Healthcare and Life Sciences
This field is ready for AI’s disruptive influence. The proliferation of electronic health records and digitised medical data presents a goldmine for AI analysis, allowing for more precise diagnoses, personalised treatments, and predictive healthcare.
The increased demand for telemedicine and remote patient monitoring drives the need for artificial intelligence (AI) systems that improve virtual care delivery and patient outcomes.
Furthermore, AI can optimise resource allocation, streamline procedures, and increase efficiency in healthcare systems.
3. Overall Software Adoption
Software is expected to be the largest AI market sector due to its role in enabling a wide range of AI applications across industries.
This comprises discriminative AI which excels at tasks such as categorisation and prediction, as well as generative AI which creates new content.
These capabilities are critical for a variety of industries, improving efficiency, decision-making, and consumer engagement with AI development services.
The increased requirement for adaptable and scalable AI software solutions makes it an important driver of AI adoption.
Why Generative AI is Important
It is important to understand the pros and cons of generative artificial intelligence (GenAI) to understand how it can fit into current and future business models and processes.
This will help to experiment productively with different scenarios of its application.
Benefits of Generative AI Business Solutions:
• GenAI accelerates product creation and improvement.
• GenAI helps personalise and make customer interactions more efficient.
• Automating routine tasks and helping with complex tasks increases employee productivity.
• GenAI can automatically generate articles, reports and marketing materials.
• GenAI improves help desk and knowledge management systems.
• GenAI can change the tone of text to suit different audiences.
• GenAI reduces large amounts of information to key points.
• GenAI makes complex information more accessible.
• GenAI organises content for specific tasks.
• GenAI makes chatbots more responsive and accurate.
• GenAI helps generate and debug code.
• GenAI helps develop new products based on data analysis.
• GenAI optimises business processes to improve efficiency.
• GenAI helps in analysing and interpreting data.
• GenAI offers personalised recommendations based on user preferences and behaviour.
Learn more about AI development services.
Contact us →What are Some Limitations of AI Implementation
Artificial intelligence (AI) is all around us, but its capabilities are often overestimated. One major problem is the huge amounts of data needed to train models.
Collecting and partitioning this data is difficult and expensive. Even when the data is there, AI operates as a black box without explaining its decisions. This limits the use of AI in important areas such as healthcare and law.
Another challenge is interpreting AI decisions. Current deep learning techniques, such as neural networks, require a lot of effort to create accurate models.
Such systems are not directly programmed but rather trained, making them difficult to customise for specific tasks.
Data often needs to be manually labelled, which requires a lot of human resources. Therefore, companies face significant organisational hurdles when implementing AI solutions.
These limitations cause frustration when attempts to implement AI meet practical barriers. Cultural barriers and a shortage of skilled personnel also complicate the process.
The growing gap between leaders and laggards in AI adoption emphasises the importance of an informed approach. You need to understand not only AI’s capabilities but also its limitations.
This will help you use AI effectively in your company, taking into account both technical and organisational aspects.
Risks of generative AI:
• Difficulties in understanding and explaining AI decisions.
• Possible errors and inaccuracies in the generated content.
• AI can generate plausible but incorrect or meaningless results.
• Risk of reinforcing biases present in training data.
• Unintentional disclosure or misuse of sensitive information.
• Increased vulnerabilities to cyber threats.
How Computools Can Help Your Business
Generative AI for businesses offers a wide range of potential, as well as numerous implementation approaches.
These approaches span the range, from purchasing pre-built apps and customizing foundation models to creating AI models from the ground up. Given this intricacy, it is critical to take an organised approach.
This systematic method should include the following critical steps:
1. Strategic ideation and prioritisation
We will collaborate closely with your business and IT teams to develop a comprehensive set of generative AI use cases consistent with your strategic goals.
We’ll next assist you in prioritising these use cases based on their potential business value and feasibility, ensuring that you focus on the most significant prospects first.
2. Expert Team Formation
We will form a dedicated “fusion team” for your generative AI pilot project. This team will have various Computools expertise, including commercial partners, software developers, and AI experts. This ensures that you have the necessary skills at all project stages.
3. Streamlined Pilot Design & Planning
Our team will work with you to create a clear plan for your pilot project. This strategy will revolve around developing a Minimum Viable Product (MVP) to validate the possible value proposition for your customers or employees.
We’ll also provide clear deployment methodologies and risk mitigation techniques for speedy testing and evaluation of potential improvements in your key business KPIs.
3. MVP Implementation and Continuous Improvement
We will oversee the delivery of your MVP, ensuring that it includes the bare minimum of functionality required to test your use cases and refine your assumptions about scaling costs and value.
Following the pilot, we will review the outcomes to decide whether to cease, refine, or scale each use case. We aim to use early accomplishments to assist you in broadening the scope of your generative AI for businesses journey.
Partnering with Computools gives you access to our knowledge and a disciplined approach to leveraging generative AI opportunities.
This allows you to focus on what is most important: achieving your strategic goals and generating business success with the help of this breakthrough technology.
Our comprehensive AI development services encompass the entire generative AI lifecycle, from ideation and pilot development to full-scale implementation and ongoing optimisation.
We’ll work alongside your team to ensure a smooth integration of generative AI into your existing workflows, maximising its impact and accelerating your path to success.
Want to learn how Generative AI can transform your business? Contact us at info@computools.com to discuss opportunities and strategies for implementing software solutions for your company.
THE AUTHOR:
Computools was selected through an RFP process. They were shortlisted and selected from between 5 other suppliers. Computools has worked thoroughly and timely to solve all security issues and launch as agreed. Their expertise is impressive.