AI Writing Assistants Statistics 2024 – Everything You Need to Know

Steve Bennett
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Are you looking to add AI Writing Assistants to your arsenal of tools? Maybe for your business or personal use only, whatever it is – it’s always a good idea to know more about the most important AI Writing Assistants statistics of 2024.

My team and I scanned the entire web and collected all the most useful AI Writing Assistants stats on this page. You don’t need to check any other resource on the web for any AI Writing Assistants statistics. All are here only 🙂

How much of an impact will AI Writing Assistants have on your day-to-day? or the day-to-day of your business? Should you invest in AI Writing Assistants? We will answer all your AI Writing Assistants related questions here.

Please read the page carefully and don’t miss any word. 🙂

Best AI Writing Assistants Statistics

☰ Use “CTRL+F” to quickly find statistics. There are total 178 AI Writing Assistants Statistics on this page 🙂

AI Writing Assistants Usage Statistics

  • When it comes to usage, 51% use voice assistants in the car, 6% in public, and 1.3% at work. [0]
  • AI usage statistics show that in 2030, about 26.1% of China’s GDP will come from AI. [0]
  • Global voice assistant usage during COVID 19 rose 7%. [1]

AI Writing Assistants Market Statistics

  • As a part of their marketing efforts, 47% of the more advanced enterprises have applied an AI strategy to their mobile apps; additionally, 84% use a personalized strategy. [0]
  • Only 17% of email marketers planned on using artificial intelligence in 2018. [0]
  • 87% of AI adopters said that they were using, or at least considering using, AI for sales forecasts and to improve their email marketing. [0]
  • In 2019, statistics predicted the market size would grow by 154% and continue growing by at least 120% annually. [2]
  • Artificial intelligence software market growth forecast worldwide 2019. [2]
  • StatisticsDuring the forecast period of 2017 2025, the NLP market will likely grow 14x larger. [2]
  • To enjoy the artificial intelligence market’s predicted influx of $997.77 billion in 2028 and to adapt to life alongside machines, companies will need to get with the programming. [2]
  • In 2021, business analysts estimated that the Key Statistics The U.S. artificial intelligence market size value in 2020 wasSources PR Newswire, GlobeNewsWireAI Adoption. [2]
  • During the forecast period of 2017 2025, the NLP market will likely grow 14x larger. [2]
  • In 2019, WIPO reported that AI was the most prolific emerging technology in terms of number of patent applications and granted patents, the Internet of things was estimated to be the largest in terms of market size. [3]
  • $80 million – The estimated size of the US deep learning software market by 2025. [1]
  • The projected market size of the global artificial intelligence industry as it grows the projected market size of the global artificial intelligence industry between 2019 and 2024 at a CAGR of over 33% between 2019 and 2024. [1]
  • $44.3 billion – The projected size of the global deep learning market by 2027 at a CAGR of 39.2% during the forecast period. [1]
  • $117.19 billion – The expected value of the global machine learning market by 2027 at a CAGR of 39.2% during the forecast period. [1]
  • $87.68 billion – The expected value of the artificial intelligence hardware market at a CAGR of 37.60% from 2019 to 2026. [1]
  • The estimated value of the global natural language processing market by 2026. [1]
  • 16% of IT leaders want to use ML in sales and marketing. [1]
  • For example, 47% said they were able to optimize sales and marketing, while 32% said they were able to reduce operating costs. [1]
  • 61% of marketers say AI is the most critical aspect of their data strategy. [1]
  • 87% of companies who use AI plan to use them in sales forecasting and email marketing. [1]
  • #2 61% of marketers say artificial intelligence is the most important aspect of their data strategy. [4]
  • Research from Callcredit shows that 96% of senior marketers waste an average of five hours and 36 minutes every week trying to improve their data analysis processes. [4]
  • This compares to just 10% in 2012 , revealing a new marketing channel where consumers can be reached while they’re on the road. [4]
  • 87% of current AI adopters said they were using or considering using AI for sales forecasting and for improving e. [4]
  • This number will reach 7 billion by 2020, according to IHS Markit, which shows where the latest emerging consumer market lies. [4]
  • The intelligent virtual assistant market size was valued at $ 3,442 billion in 2019, and is projected to reach $ 44,255 million by 2027, growing at a CAGR of 37.7% from 2020 to 2027. [5]

AI Writing Assistants Software Statistics

  • Artificial intelligence software market growth forecast worldwide 2019. [2]
  • $80 million – The estimated size of the US deep learning software market by 2025. [1]

AI Writing Assistants Adoption Statistics

  • According to AI stats in 2020, nearly 30% of AI adoption in manufacturing goes to maintenance. [0]
  • ) Forrester has forecasted a few of the major AI adoption statistics, saying that cognitive technologies like AI will also create a few jobs; however, even with that addition, automation will replace a net of 7% of US jobs by 2025. [0]
  • Among the biggest challenges to machine learning adoption include scaling up (43%), versioning of ML models (41%). [1]

AI Writing Assistants Latest Statistics

  • AI can increase business productivity by 40%. [0]
  • Already 77% of the devices we use feature one form of AI or another. [0]
  • AI technology can enhance business productivity by up to 40%. [0]
  • AI will enable people to use their time efficiently, which will increase their productivity by 40%. [0]
  • Businesses with more than 100,000 employees are more likely to have a strategy that implements AI. [0]
  • 47% of established organizations have a defined AI strategy for mobile. [0]
  • 41% of consumers believe artificial intelligence will improve their lives in some way. [0]
  • Only 33% of consumers think they’re already using AI platforms. [0]
  • This is one of the more interesting AI facts; only 33% think that they use technology that features artificial intelligence. [0]
  • In reality, 77% use an AI. [0]
  • 84% of global business organizations believe that AI will give them a competitive advantage. [0]
  • 84% of business organizations will adopt AI because it gives them a competitive advantage over their rivals. [0]
  • That is the conclusion, according to a 2017 artificial intelligence Statista study. [0]
  • 17% of in company respondents and 21% of agencies planned to innovate with AI in 2018. [0]
  • 97% of mobile users are already using AI. [0]
  • According to a study by IDAP, only 2% of iPhone owners have never used Siri, and only 4% of Android owners have never leveraged the power of OK Google. [0]
  • 40% of people use the voice search function at least once every day. [0]
  • 30% of web browsing and searches were done without a screen by the end of 2020. [0]
  • A 2017 Pew Research study showed that 46% of Americans use digital assistants to interact with their smartphones. [0]
  • Voice assistants are present on a diverse range of devices, so 42% of users have the tech on their smartphones, 14% of them use it on a computer or tablet, while 8% of them use it on a standalone device such as Amazon Echo or Google Home. [0]
  • Google’s Machine Learning Program is 89% accurate. [0]
  • With 89% accuracy, Google’s deep learning program is 15% more effective than pathologists. [0]
  • Customers will give up on a search after 90 seconds, according to research conducted by Netflix, supported by other artificial intelligence statistics from 2017. [0]
  • 36% of executives say that their primary goal for incorporating AI is to optimize internal business operations. [0]
  • 20% of C suite uses machine learning. [0]
  • A paper by McKinsey shows that 20% of C level executives across ten countries consider machine learning to be a core part of their business. [0]
  • Intelligent robots could replace 30% of the human workforce globally by 2030. [0]
  • According to AI technology statistics, robotics could replace about 800 million jobs, making about 30% of occupations extinct. [0]
  • 52% of experts believe that as much as automation will displace people from their careers, they will still innovate more jobs. [0]
  • About 250 million cars were predicted to have an Internet connection by the end of 2020. [0]
  • Experts predicted that internet enabled vehicles will reach 250 million by the end of 2020. [0]
  • Machine and asset maintenance in manufacturing takes 29% of AI automation. [0]
  • AI implementation in consumer packaged goods has led to a 20% reduction in forecast errors. [0]
  • 70% of manufacturers still haven’t adopted digital operating systems. [0]
  • However, 30% of companies using this digital innovation say that it has generated value in terms of relationships between customers and suppliers. [0]
  • Automation could free up 10% of nursing activities by 2030. [0]
  • AI in medicine statistics show that humans will still do 90% of nursing activities by 2030. [0]
  • In 2021, 73% of retailers planned to introduce AI to optimize their pricing. [0]
  • 75% of companies plan to use AI systems to eliminate fraud. [0]
  • Money lost to fraudsters was predicted to reach $35 billion by 2020. [0]
  • AI will grow at a CAGR of 35.9% by 2025. [0]
  • With machine learning, Amazon reduced its “click to ship” time to 15 minutes, a 225% decrease. [0]
  • With Kiva, the average clickto ship time is 15 minutes, which is a 225% improvement from where it was. [0]
  • Statista conducted an online survey of 1,028 respondents in 2017 and found that 61% of them were planning to use AI for sales forecasting. [0]
  • 85% of customers’ relationships with business enterprises will be managed without human involvement. [0]
  • 67% of people expect to use messaging apps to talk to a business, which makes chatbots quite significant. [0]
  • 38% of consumers on a global level prefer to use chatbots. [0]
  • A survey of 5,000 consumers across six countries found that 38% rated their overall perception of chatbots as positive. [0]
  • 11% had a negative perception, while 51% gave a neutral statement. [0]
  • Forecasts predicted that drivers of AI, such as Natural Language Processing , computer vision, and machine learning, to reach nearly $23 billion in growth by Q4 of 2020. [0]
  • According to AI growth statistics, the industry will grow from $5 billion in 2015 to about $125 billion in 2025. [0]
  • AI will contribute to 26% of China’s Gross Domestic Product in 2030. [0]
  • The technology contribution to other global economies will be North America 14.5%, followed closely by the United Arab Emirates with 13.5%. [0]
  • 27% of executives say that their organization plans to invest in AI cybersecurity safeguards. [0]
  • 40% of digital transformations and 100% of initiatives based on the internet of things will be supported by AI. [0]
  • 72% of execs believe that AI will be the most significant business advantage of the future. [0]
  • AI will increase labor productivity and optimize business efficiency by 67%, automate communication by 70%, and improve data analytics by 59%, according to AI predictions 46. [0]
  • AI will automate 16% of American jobs. [0]
  • Machine learning is predicted to grow by 48% in the automotive industry. [0]
  • With this, the compound annual growth could increase by 48.3%. [0]
  • 15% of enterprises are using AI, and 31% of them say that it is their agenda for the next 12 months. [0]
  • So by 2020, according to these AI stats, there are chances that the brands offering a customer centric experience will see more success, revenue, and profit. [0]
  • AI statistics predicted financial services companies to spend $11 billion on artificial intelligence in 2020. [0]
  • According to a study by Gartner, 37% of businesses did so in 2019. [6]
  • Grammarly is like a little superpower, especially when I need to be at 110%.”. [7]
  • Finish your first draft Speed up your content pipeline by writing 80% by Jasper and 20% edited by humans. [8]
  • You can expect global artificial intelligence to expand at a CAGR of 40.2% from 2021 to 2028.seems like it won’t be slowing down anytime soon. [2]
  • Statista, Statista, We ForumHow Businesses Adopt Artificial IntelligenceAI Adoption in BusinessA whopping 83% of companies share that using AI in their business strategies is a top priority. [2]
  • estate1.70%28.20%Water, sewage and waste management0.60%62.60%Agriculture, forestry and fishing1.10%18.70%Electricity and gas supply0.40%31.80%Mining. [2]
  • experience57%34%Retaining customers31%29%Interacting with customers48%28%Recommender systems27%27%Detecting fraud46%27%Reducing customer. [2]
  • churn22%26%Acquiring new customers34%26%Increasing customer loyalty40%20%Increasing long term customer engagement44%19%Building brand awareness31%14%Other1%15%Key Statistics. [2]
  • A whopping 83% of companies share that using AI in their business strategies is a top priority. [2]
  • Tech companies investing in AI Share of questions answered correctly by selected digital assistants as of 2019, by category Type of questionGoogle AssistantSiriAlexaLocal93%89%85%Commerce92%68%71%Navigation98%86%72%Information96%76%93%Command86%93%69%. [2]
  • Employment shares and the estimated proportion of jobs at potential high risk of automation by early 2030s for all UK industry sectors IndustryEmployment share of total jobs (%). [2]
  • churn22%26%Acquiring new customers34%26%Increasing customer loyalty40%20%Increasing long term customer engagement44%19%Building brand. [2]
  • 26% 40% 20% 44% 19% 31% 14% 1% 15%. [2]
  • Simon predicted, “machines will be capable, within twenty years, of doing any work a man can do”.[31]Marvin Minsky agreed, writing, “within a generation … [3]
  • [41] Faster computers, algorithmic improvements, and access to large amounts of data enabled advances in machine learning and perception; data hungry deep learning methods started to dominate accuracy benchmarks around 2012.According to [42]. [3]
  • DeepMind’s [156] Computer visionrepresents 49 percent of patent families related to a functional application in 2016. [3]
  • See table 4; 9% is both the OECD average and the US average.[200] Rodney Brookswrites, “I think it is a mistake to be worrying about us developing malevolent AI anytime in the next few hundred years. [3]
  • Global revenue for AI hardware, particularly in the chip business, fell by 12% due to the impact of COVID. [1]
  • People who used it several times a day rose to 25% in MarchApril 2020 from 20% back in December 2019. [1]
  • 80.5% of under 30 consumers use a voice assistant on smartphones compared to 60.5% of the oldest age group. [1]
  • 74.7% of consumers ages 3044 use voice assistants on smartphones, while 68.8% of consumers ages 45. [1]
  • It’s predicted that 8 billion people will be using voice assistants by 2024. [1]
  • 50% of respondents said that their companies have adopted AI in at least one business function. [1]
  • 25% of IT leaders plan to use ML for security purposes. [1]
  • For example, 80% of people said that AI has helped increase revenue. [1]
  • Advancements in AI and machine learning have the potential to increase global GDP by 14% from now until 2030. [1]
  • 49% of companies are exploring or planning to use ML. [1]
  • 51% of organizations claim to be early adopters of ML. [1]
  • 15% of organizations are already advanced ML users. [1]
  • 75% of AI projects are now under the leadership of C. [1]
  • 91.5% of leading businesses have ongoing investments in AI. [1]
  • 62% of customers are willing to submit their data to AI to improve their experience with businesses. [1]
  • Tesla has logged an estimated 1.88 billion in autonomous miles as of October 2019. [1]
  • 80% of companies plan to adopt AI for customer service by 2020. [1]
  • Only 14.6% of businesses reported that they have deployed AI capabilities into widespread production. [1]
  • 60% of consumers had a lukewarm acceptance of an AI. [1]
  • When it comes to resolving customer issues, 41% of consumers said they wanted them resolved by a human agent. [1]
  • 60% – the reduction in translation errors of Google Translate when it changed to GNMT a translation algorithm powered by machine learning. [1]
  • Machine learning methods used to predict the mortality of COVID 19 patients demonstrated 92% accuracy. [1]
  • 5% The error rate of speech recognition systems. [1]
  • 40% of the annual value created by analytics is made up of deep learning techniques. [1]
  • 46.8% – the accuracy of Google’s machine learningpowered lipreading system , which topples a professional human lip readers 12.4% accuracy. [1]
  • #3 80% of business and tech leaders say AI already boosts productivity Source. [4]
  • According to Creative Strategies, only 2% of iPhone users have never used Siri and just 4% of Android users have never used Google Assistant. [4]
  • By 2020, 30% of companies worldwide will be using AI in at least one of their sales processes. [4]
  • #18 20% of the CSuite is already using machine learning #19 The three most in demand skills on Monster.com are machine learning , deep learning and natural language processing. [4]
  • According to Salesforce’s 2016 Connected Customer report, companies will need accurate prediction models to anticipate the needs of buyers – or risk losing them to another brand. [4]
  • #22 Business execs are turning to AI to cut out repetitive tasks such as paperwork (82%), scheduling (79%) and timesheets (78%). [4]
  • #24 61% of companies with an innovation strategy are using AI to identify new opportunities Source. [4]
  • According to Pega, only 33% of consumers think they’re using AI powered technology while 77% are already using AI platforms. [4]
  • With machine learning, Amazon has reduced the time between users clicking the buy button and their items being shipped to just 15 minutes on average – a 225% reduction, according to Wolfstat. [4]
  • By 2019, 40% of digital transformation initiatives – and 100% of IoT initiatives – will be supported by AI capabilities Source. [4]
  • According to Statista, 61% of companies using AI are already using the technology – or plan to use it – for sales forecasting. [4]
  • #36 80% of businesses plan to adopt AI as a customer service solution by 2020. [4]
  • #46 45% of end users prefer chatbots as the primary mode of communication for customer service inquiries. [4]
  • Only 20% of executives feel their data science teams are ready for AI, while 19% have no data science team at all. [4]
  • According to G∗Power, the desired total sample size was 109. [9]
  • Therefore, 120 participants recruited, allowing for a 10% loss of data .2.4.2. [9]
  • The AI included 52% women and 48% men. [9]
  • Also, AI group consists of 28.3% in humanity sciences, 28.3% technology sciences, and 43.3% health sciences. [9]
  • The NEAI included 46.7% females and 53.3% males. [9]
  • Also, NEAI group consists of 20 % in humanity sciences, 41.7% technology sciences, and 38.3% health sciences. [9]
  • Nine (20%). [9]
  • Also, 30% of the NEAI group dropped out post. [9]
  • Finally, 30% 77.5% of all participants completed the study. [9]
  • 4.50, p < .001, and Cohen’s d = −.82, 95% CI [−1.20, −.45]. [9]
  • 4.79, p < .001, and Cohen’s d = . 54, 95% CI [.18, .91].Academic emotion results for positive academic emotion, The results revealed a statistically significant main effect for group, F=. [9]
  • and Cohen’s d = −.98, 95% CI [−1.36, −.60]. [9]
  • In English writing, learners with higher self efficacy levels are more likely to put more effort, exert more persistence, and thus have higher writing outcomes. [9]
  • According to the pedagogical approach related to sustainability, current assessment in higher education is inadequate to prepare students for a lifetime of learning. [9]
  • Over 40% of students were recruited in the first five weeks, 70% by Week 10, and the rest by Week 14. [9]
  • Therefore, 120 participants recruited, allowing for a 10% loss of data. [9]
  • 4.79, p < .001, and Cohen’s d = . 54, 95% CI [.18, .91]. [9]
  • GPT 3 had been trained on around 200 billion words, at an estimated cost of tens of millions of dollars. [10]
  • People averaged 35% across the tasks ; answering randomly would score 25%. [10]
  • When GPT3 was shown just the questions, it scored 38%; in a ‘few shot’ setting , it scored 44%. [10]
  • In fact, Ramirez says that using AI writing tools to outline his blog posts and expand on his ideas has helped him cut down on 80% to 90% of content creation time. [11]
  • Not only does it create original content, according to the company, but it also supports over 25 languages. [11]
  • This tool claims it can speed up content creation by 50% with its automatic content writing and article rewording features. [11]
  • Intelligent Virtual Assistant Market AsiaPacific would exhibit the highest CAGR of 40.9% during 2020. [5]
  • In addition, banking clients who have implemented intelligent virtual assistant in their operations have affected a 46% improvement in customer handling. [5]

I know you want to use AI Writing Assistants, thus we made this list of best AI Writing Assistants. We also wrote about how to learn AI Writing Assistants and how to install AI Writing Assistants. Recently we wrote how to uninstall AI Writing Assistants for newbie users. Don’t forgot to check latest AI Writing Assistantsstatistics of 2024.

Reference


  1. techjury – https://techjury.net/blog/ai-statistics/.
  2. financesonline – https://financesonline.com/machine-learning-statistics/.
  3. explodingtopics – https://explodingtopics.com/blog/ai-statistics.
  4. wikipedia – https://en.wikipedia.org/wiki/Artificial_intelligence.
  5. ventureharbour – https://www.ventureharbour.com/marketing-ai-machine-learning-statistics/.
  6. alliedmarketresearch – https://www.alliedmarketresearch.com/intelligent-virtual-assistant-market.
  7. dataprot – https://dataprot.net/statistics/ai-statistics/.
  8. grammarly – https://www.grammarly.com/.
  9. jasper – https://www.jasper.ai/.
  10. sciencedirect – https://www.sciencedirect.com/science/article/pii/S2405844021011178.
  11. nature – https://www.nature.com/articles/d41586-021-00530-0.
  12. hubspot – https://blog.hubspot.com/marketing/ai-writing-tools-blogging.

How Useful is Ai Writing Assistants

AI Writing Assistants: Transforming the Future of Writing

Pioneering advancements in computing and artificial intelligence have undoubtedly changed multiple facets of our lives. From the momentous transformations in data analysis, autonomous vehicles, and virtual assistants, AI has emerged as a game-changer across various industries. In the realm of writing, particularly journalism and content creation, the introduction of AI writing assistants has sparked considerable debate and intrigue. Stemming from the forefront of technological innovation, these assistants offer a range of features designed to enhance our writing abilities. However, the question that lingers is: How useful are these AI writing assistants, and what impact do they have in the world of writing?

First and foremost, the indispensable value that AI writing assistants bring to the table is their ability to streamline the writing process. Considerably reducing the time it takes to produce coherent and grammatically correct text, these assistants act as quasi-editors and grammar police, effortlessly highlighting potential errors and suggesting alterations for enhanced clarity. As a result, writers can focus their energy on refining their ideas and generating insightful content, leveraging the AI assistants to brush away linguistic pitfalls.

Furthermore, AI writing assistants can educate, nurture, and empower writers. With every interaction, these assistants learn from their users, adapting to individual needs and preferences, and sharpening their capacity to provide tailored suggestions. Undoubtedly, this functionality helps enhance writers’ skills, making them more conscious of their syntax, vocabulary, and expressive potential. It is through this interactive relationship that writers can gain immense value from AI writing assistants as they explore new perspectives and elevate their prose.

Moreover, by incorporating AI writing assistants into our creative process, we can break through the limitations of writer’s block or lack of inspiration. These partners in productivity can lend supportive ideas, offer synonyms to avoid overused aspects of our writing, and even assist in reorganization for better coherence. By revolutionizing the collaboration between human intellect and computing ingenuity, AI writing assistants extend their assistance to both newcomers and veteran writers alike, amplifying creative thinking and fostering exploration of unique angles.

Nevertheless, it is essential not to overlook the intrinsic role of human creativity and intuition in the world of literature, journalism, and more generally, writing. While AI writing assistants offer invaluable tools that technical writers or those seeking concise messaging may find particularly appealing, these assistive technologies have their limitations in capturing the heart and soul of expression. Where AI may excel in rule-based editing and linguistic analysis, it often falls short in replicating the distinctive voice, raw emotion, and subtle nuances that humans effortlessly infuse into their writing.

Hence, it is crucial to view AI writing assistants as aides and collaborators rather than as replacements. These technological marvels undoubtedly contribute to the evolution of writing, making the process more efficient, accessible, and user-friendly. However, let us not forget that the soul of writing lies in the genuine human experience, the depth of thought, and the emotions that weaves an intangible connection between the author and the reader.

In conclusion, AI writing assistants stand as powerful allies to writers, significantly enhancing productivity, focusing on quality, and nurturing editorial skills. Their efficiency and functionality grant writers the freedom to direct their energies towards more intellectually demanding aspects of the craft. Nevertheless, it is crucial to maintain a balance, recognizing the value of human creativity and surrendering to the organic empowerment that technology offers. Together, we can embark on a remarkable journey where the synergy of humans and machines harmoniously shapes the future of writing.

In Conclusion

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